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Author : Adrian Rodney Pagan,Vance L. Martin
Publisher : Unknown
Page : 39 pages
File Size : 45,6 Mb
Release : 1996
Category : Econometric models
ISBN : 073251391X
Author : Roberto Mariano,Til Schuermann,Melvyn J. Weeks
Publisher : Cambridge University Press
Page : 488 pages
File Size : 45,9 Mb
Release : 2000-07-20
Category : Business & Economics
ISBN : 0521591120
This substantial volume has two principal objectives. First it provides an overview of the statistical foundations of Simulation-based inference. This includes the summary and synthesis of the many concepts and results extant in the theoretical literature, the different classes of problems and estimators, the asymptotic properties of these estimators, as well as descriptions of the different simulators in use. Second, the volume provides empirical and operational examples of SBI methods. Often what is missing, even in existing applied papers, are operational issues. Which simulator works best for which problem and why? This volume will explicitly address the important numerical and computational issues in SBI which are not covered comprehensively in the existing literature. Examples of such issues are: comparisons with existing tractable methods, number of replications needed for robust results, choice of instruments, simulation noise and bias as well as efficiency loss in practice.
Author : Jushan Bai,Serena Ng
Publisher : Now Publishers Inc
Page : 90 pages
File Size : 46,5 Mb
Release : 2008
Category : Business & Economics
ISBN : 9781601981448
Large Dimensional Factor Analysis provides a survey of the main theoretical results for large dimensional factor models, emphasizing results that have implications for empirical work. The authors focus on the development of the static factor models and on the use of estimated factors in subsequent estimation and inference. Large Dimensional Factor Analysis discusses how to determine the number of factors, how to conduct inference when estimated factors are used in regressions, how to assess the adequacy pf observed variables as proxies for latent factors, how to exploit the estimated factors to test unit root tests and common trends, and how to estimate panel cointegration models.
Author : Anonim
Publisher : Emerald Group Publishing
Page : 688 pages
File Size : 43,6 Mb
Release : 2016-01-08
Category : Business & Economics
ISBN : 9781785603525
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.
Author : Fabio Canova
Publisher : Princeton University Press
Page : 512 pages
File Size : 46,5 Mb
Release : 2011-09-19
Category : Business & Economics
ISBN : 9781400841028
The last twenty years have witnessed tremendous advances in the mathematical, statistical, and computational tools available to applied macroeconomists. This rapidly evolving field has redefined how researchers test models and validate theories. Yet until now there has been no textbook that unites the latest methods and bridges the divide between theoretical and applied work. Fabio Canova brings together dynamic equilibrium theory, data analysis, and advanced econometric and computational methods to provide the first comprehensive set of techniques for use by academic economists as well as professional macroeconomists in banking and finance, industry, and government. This graduate-level textbook is for readers knowledgeable in modern macroeconomic theory, econometrics, and computational programming using RATS, MATLAB, or Gauss. Inevitably a modern treatment of such a complex topic requires a quantitative perspective, a solid dynamic theory background, and the development of empirical and numerical methods--which is where Canova's book differs from typical graduate textbooks in macroeconomics and econometrics. Rather than list a series of estimators and their properties, Canova starts from a class of DSGE models, finds an approximate linear representation for the decision rules, and describes methods needed to estimate their parameters, examining their fit to the data. The book is complete with numerous examples and exercises. Today's economic analysts need a strong foundation in both theory and application. Methods for Applied Macroeconomic Research offers the essential tools for the next generation of macroeconomists.
Author : Gabriele Fiorentini,Enrique Sentana
Publisher : Unknown
Page : 0 pages
File Size : 54,9 Mb
Release : 2001
Category : Electronic
ISBN : OCLC:1375619832
We investigate the effects of dynamic heteroskedasticity on statistical factor analysis. We show that identification problems are alleviated when variation in factor variances is accounted for. Our results apply to dynamic APT models and other structural models. We also find that traditional ML estimation of unconditional variance parameters remains consistent if the factor loadings are identified from the unconditional distribution, but their standard errors must be robustified. We develop a simple preliminary LM test for ARCH effects in the common factors, and discuss two-step consistent estimation of the conditional variance parameters. Finally, we conduct a detailed simulation exercise.
Author : Christian Gourieroux,Alain Monfort
Publisher : Oxford University Press
Page : 185 pages
File Size : 40,8 Mb
Release : 1996
Category : Business & Economics
ISBN : 9780198774754
High speed computing has enabled a new generation of statistical econometrics to become available. The simulation of problems that previously were too unwieldy to solve because of large integrals is now possible.
Author : Vance Martin,Stan Hurn,David Harris
Publisher : Cambridge University Press
Page : 925 pages
File Size : 41,7 Mb
Release : 2013
Category : Business & Economics
ISBN : 9780521139816
"Maximum likelihood estimation is a general method for estimating the parameters of econometric models from observed data. The principle of maximum likelihood plays a central role in the exposition of this book, since a number of estimators used in econometrics can be derived within this framework. Examples include ordinary least squares, generalized least squares and full-information maximum likelihood. In deriving the maximum likelihood estimator, a key concept is the joint probability density function (pdf) of the observed random variables, yt. Maximum likelihood estimation requires that the following conditions are satisfied. (1) The form of the joint pdf of yt is known. (2) The specification of the moments of the joint pdf are known. (3) The joint pdf can be evaluated for all values of the parameters, 9. Parts ONE and TWO of this book deal with models in which all these conditions are satisfied. Part THREE investigates models in which these conditions are not satisfied and considers four important cases. First, if the distribution of yt is misspecified, resulting in both conditions 1 and 2 being violated, estimation is by quasi-maximum likelihood (Chapter 9). Second, if condition 1 is not satisfied, a generalized method of moments estimator (Chapter 10) is required. Third, if condition 2 is not satisfied, estimation relies on nonparametric methods (Chapter 11). Fourth, if condition 3 is violated, simulation-based estimation methods are used (Chapter 12). 1.2 Motivating Examples To highlight the role of probability distributions in maximum likelihood estimation, this section emphasizes the link between observed sample data and 4 The Maximum Likelihood Principle the probability distribution from which they are drawn"-- publisher.
Author : G. Gregoriou,R. Pascalau
Publisher : Springer
Page : 257 pages
File Size : 55,7 Mb
Release : 2010-12-13
Category : Business & Economics
ISBN : 9780230298101
This book proposes new methods to build optimal portfolios and to analyze market liquidity and volatility under market microstructure effects, as well as new financial risk measures using parametric and non-parametric techniques. In particular, it investigates the market microstructure of foreign exchange and futures markets.
Author : Anonim
Publisher : Unknown
Page : 904 pages
File Size : 44,9 Mb
Release : 2004
Category : Mathematics
ISBN : UOM:39015059777667
Author : Sylvia Kaufmann
Publisher : Unknown
Page : 64 pages
File Size : 41,7 Mb
Release : 2016
Category : Electronic
ISBN : OCLC:1306009561
This paper considers factor estimation from heterogenous data, where some of the variables are noisy and only weakly informative for the factors. To identify the irrelevant variables, we search for zero rows in the loadings matrix of the factor model. To sharply separate these irrelevant variables from the informative ones, we choose a Bayesian framework for factor estimation with sparse priors on the loadings matrix. The choice of a sparse prior is an extension to the existing macroeconomic literature, which predominantly uses normal priors on the loadings. Simulations show that the sparse factor model can well detect various degrees of sparsity in the data, and how irrelevant variables can be identified. Empirical applications to a large multi-country GDP dataset and disaggregated CPI inflation data for the US reveal that sparsity matters a lot, as the majority of the variables in both datasets are irrelevant for factor estimation.
Author : Jörg Breitung
Publisher : Unknown
Page : 40 pages
File Size : 54,6 Mb
Release : 2016
Category : Electronic
ISBN : OCLC:1306165675
Factor models can cope with many variables without running into scarce degrees of freedom.
Author : Christian Gouriéroux,Alain Monfort
Publisher : OUP Oxford
Page : 190 pages
File Size : 45,7 Mb
Release : 1997-01-09
Category : Business & Economics
ISBN : 9780191525094
This book introduces a new generation of statistical econometrics. After linear models leading to analytical expressions for estimators, and non-linear models using numerical optimization algorithms, the availability of high- speed computing has enabled econometricians to consider econometric models without simple analytical expressions. The previous difficulties presented by the presence of integrals of large dimensions in the probability density functions or in the moments can be circumvented by a simulation-based approach. After a brief survey of classical parametric and semi-parametric non-linear estimation methods and a description of problems in which criterion functions contain integrals, the authors present a general form of the model where it is possible to simulate the observations. They then move to calibration problems and the simulated analogue of the method of moments, before considering simulated versions of maximum likelihood, pseudo-maximum likelihood, or non-linear least squares. The general principle of indirect inference is presented and is then applied to limited dependent variable models and to financial series.
Author : Christian Gourieroux,Joann Jasiak
Publisher : Princeton University Press
Page : 528 pages
File Size : 40,7 Mb
Release : 2022-12-13
Category : Business & Economics
ISBN : 9780691242361
Financial econometrics is a great success story in economics. Econometrics uses data and statistical inference methods, together with structural and descriptive modeling, to address rigorous economic problems. Its development within the world of finance is quite recent and has been paralleled by a fast expansion of financial markets and an increasing variety and complexity of financial products. This has fueled the demand for people with advanced econometrics skills. For professionals and advanced graduate students pursuing greater expertise in econometric modeling, this is a superb guide to the field's frontier. With the goal of providing information that is absolutely up-to-date—essential in today's rapidly evolving financial environment—Gourieroux and Jasiak focus on methods related to foregoing research and those modeling techniques that seem relevant to future advances. They present a balanced synthesis of financial theory and statistical methodology. Recognizing that any model is necessarily a simplified image of reality and that econometric methods must be adapted and applied on a case-by-case basis, the authors employ a wide variety of data sampled at frequencies ranging from intraday to monthly. These data comprise time series representing both the European and North American markets for stocks, bonds, and foreign currencies. Practitioners are encouraged to keep a critical eye and are armed with graphical diagnostics to eradicate misspecification errors. This authoritative, state-of-the-art reference text is ideal for upper-level graduate students, researchers, and professionals seeking to update their skills and gain greater facility in using econometric models. All will benefit from the emphasis on practical aspects of financial modeling and statistical inference. Doctoral candidates will appreciate the inclusion of detailed mathematical derivations of the deeper results as well as the more advanced problems concerning high-frequency data and risk control. By establishing a link between practical questions and the answers provided by financial and statistical theory, the book also addresses the needs of applied researchers employed by financial institutions.
Author : John Creedy,Vance Martin
Publisher : Edward Elgar Publishing
Page : 312 pages
File Size : 46,6 Mb
Release : 1997
Category : Business & Economics
ISBN : STANFORD:36105022825264
A sequel to Creedy and Martin's (eds.) Chaos and Nonlinear Models (1994). Compiles recent developments in such techniques as cross- sectional studies of income distribution and discrete choice models, time series models of exchange rate dynamics and jump processes, and artificial neural networks and genetic algorithms of financial markets. Also considers the development of theoretical models and estimating and testing methods, with a wide range of applications in microeconomics, macroeconomics, labor, and finance. Annotation copyrighted by Book News, Inc., Portland, OR