Bayesian estimation of dsge models, Herbst, Edward P. Schorfheide, Frank
Автор: Celso Jose Costa Название: Understanding DSGE models ISBN: 1622731336 ISBN-13(EAN): 9781622731336 Издательство: Неизвестно Рейтинг: Цена: 13058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Dimitris Korobilis, Kenichi Shimizu Название: Bayesian Approaches to Shrinkage and Sparse Estimation ISBN: 1638280347 ISBN-13(EAN): 9781638280347 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 13028.00 р. Наличие на складе: Поставка под заказ.
Описание: Introduces the reader to the world of Bayesian model determination by surveying modern shrinkage and variable selection algorithms and methodologies. Bayesian inference is a natural probabilistic framework for quantifying uncertainty and learning about model parameters.
Автор: Erricos Kontoghiorghes Название: Parallel Algorithms for Linear Models ISBN: 1461370647 ISBN-13(EAN): 9781461370642 Издательство: Springer Рейтинг: Цена: 12196.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The practical issues of the parallel algorithms and the theoretical aspects of the numerical methods will be of interest to a broad range of researchers working in the areas of numerical and computational methods in statistics and econometrics, parallel numerical algorithms, parallel computing and numerical linear algebra.
Описание: These essays in honor of Professor Gerhard Tintner are substantive contributions to three areas of econometrics, (1) economic models and applications,. " Professor Tintner`s career to date has spanned the organizational life of the Econometric Society and his contributions have been nearly coextensive with its scope.
Описание: A new procedure for the maximum-likelihood estimation of dynamic econometric models with errors in both endogenous and exogenous variables is presented in this monograph. A complete analytical development of the expressions used in problems of estimation and verification of models in state-space form is presented.
Автор: Erricos Kontoghiorghes Название: Parallel Algorithms for Linear Models ISBN: 0792377206 ISBN-13(EAN): 9780792377207 Издательство: Springer Рейтинг: Цена: 20733.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The practical issues of the parallel algorithms and the theoretical aspects of the numerical methods will be of interest to a broad range of researchers working in the areas of numerical and computational methods in statistics and econometrics, parallel numerical algorithms, parallel computing and numerical linear algebra.
Автор: M.J. Vilares Название: Structural Change in Macroeconomic Models ISBN: 9401084424 ISBN-13(EAN): 9789401084420 Издательство: Springer Рейтинг: Цена: 10610.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book investigates several competing forecasting models for interest rates, financial returns, and realized volatility, addresses the usefulness of nonlinear models for hedging purposes, and proposes new computational techniques to estimate financial processes.
Описание: This book explores widely used seasonaladjustment methods and recent developments in real time trend-cycle estimation.It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATSand STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate eachmethod and real data examples can be followed throughout the text. Thetrend-cycle estimation is presented using nonparametric techniques based onmoving averages, linear filters and reproducing kernel Hilbert spaces, takingrecent advances into account. The book provides a systematical treatment ofresults that to date have been scattered throughout the literature.Seasonal adjustment and real timetrend-cycle prediction play an essential part at all levels of activity inmodern economies. They are used by governments to counteract cyclicalrecessions, by central banks to control inflation, by decision makers forbetter modeling and planning and by hospitals, manufacturers, builders,transportation, and consumers in general to decide on appropriate action.This book appeals to practitioners ingovernment institutions, finance and business, macroeconomists, and other professionalswho use economic data as well as academic researchers in time series analysis,seasonal adjustment methods, filtering and signal extraction. It is also usefulfor graduate and final-year undergraduate courses in econometrics and timeseries with a good understanding of linear regression and matrix algebra, aswell as ARIMA modelling.
Автор: Paul P. Eggermont; Vincent N. LaRiccia Название: Maximum Penalized Likelihood Estimation ISBN: 1461417120 ISBN-13(EAN): 9781461417125 Издательство: Springer Рейтинг: Цена: 20123.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Ideal for researchers and practitioners in statistics and industrial mathematics, this book covers the theory and practice of nonparametric estimation. It is novel in its use of maximum penalized likelihood estimation and convex minimization problem theory.
This book aims to fill the gap between panel data econometrics textbooks, and the latest development on "big data", especially large-dimensional panel data econometrics. It introduces important research questions in large panels, including testing for cross-sectional dependence, estimation of factor-augmented panel data models, structural breaks in panels and group patterns in panels. To tackle these high dimensional issues, some techniques used in Machine Learning approaches are also illustrated. Moreover, the Monte Carlo experiments, and empirical examples are also utilised to show how to implement these new inference methods. Large-Dimensional Panel Data Econometrics: Testing, Estimation and Structural Changes also introduces new research questions and results in recent literature in this field.
Автор: Anatolyev, Stanislav Gospodinov, Nikolay Название: Methods for estimation and inference in modern econometrics ISBN: 1439838240 ISBN-13(EAN): 9781439838242 Издательство: Taylor&Francis Рейтинг: Цена: 16078.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Methods for Estimation and Inference in Modern Econometrics provides a comprehensive introduction to a wide range of emerging topics, such as generalized empirical likelihood estimation and alternative asymptotics under drifting parameterizations, which have not been discussed in detail outside of highly technical research papers. The book also addresses several problems often arising in the analysis of economic data, including weak identification, model misspecification, and possible nonstationarity. The book's appendix provides a review of some basic concepts and results from linear algebra, probability theory, and statistics that are used throughout the book.
Topics covered include:
Well-established nonparametric and parametric approaches to estimation and conventional (asymptotic and bootstrap) frameworks for statistical inference
Estimation of models based on moment restrictions implied by economic theory, including various method-of-moments estimators for unconditional and conditional moment restriction models, and asymptotic theory for correctly specified and misspecified models
Non-conventional asymptotic tools that lead to improved finite sample inference, such as higher-order asymptotic analysis that allows for more accurate approximations via various asymptotic expansions, and asymptotic approximations based on drifting parameter sequences
Offering a unified approach to studying econometric problems, Methods for Estimation and Inference in Modern Econometrics links most of the existing estimation and inference methods in a general framework to help readers synthesize all aspects of modern econometric theory. Various theoretical exercises and suggested solutions are included to facilitate understanding.
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