Semi-parametric Copula Sample Selection Models for Count Responses
Author: Karol Wyszynki
Publisher:
Published: 2016
Total Pages: 0
ISBN-13:
DOWNLOAD EBOOKRead and Download eBook Full
Author: Karol Wyszynki
Publisher:
Published: 2016
Total Pages: 0
ISBN-13:
DOWNLOAD EBOOKAuthor: K. Wyszynski
Publisher:
Published: 2016
Total Pages:
ISBN-13:
DOWNLOAD EBOOKAuthor: Kyungsoo Choi
Publisher:
Published: 1992
Total Pages: 292
ISBN-13:
DOWNLOAD EBOOKAuthor: Bo E. Honoré
Publisher:
Published: 2022
Total Pages: 0
ISBN-13:
DOWNLOAD EBOOKThis paper studies semiparametric versions of the classical sample selection model (Heckman (1976, 1979)) without exclusion restrictions. We extend the analysis in Honor'e and Hu (2020) by allowing for parameter heterogeneity and derive implications of this model. We also consider models that allow for heteroskedasticity and briefly discuss other extensions. The key ideas are illustrated in a simple wage regression for females. We find that the derived implications of a semiparametric version of Heckman's classical sample selection model are consistent with the data for women with no college education, but strongly rejected for women with a college degree or more.
Author: Markus Frölich
Publisher:
Published: 2002
Total Pages: 120
ISBN-13:
DOWNLOAD EBOOKAuthor: Harry Joe
Publisher: CRC Press
Published: 2014-06-26
Total Pages: 479
ISBN-13: 1466583231
DOWNLOAD EBOOKDependence Modeling with Copulas covers the substantial advances that have taken place in the field during the last 15 years, including vine copula modeling of high-dimensional data. Vine copula models are constructed from a sequence of bivariate copulas. The book develops generalizations of vine copula models, including common and structured facto
Author: Whitney K. Newey
Publisher:
Published: 2003
Total Pages: 0
ISBN-13:
DOWNLOAD EBOOKSample selection models are important for correcting for the effects of nonrandom sampling in microeconomic data. This note is about semiparametric estimation using a series approximation to the selection correction term. Regression spline and power series approximations are considered. Consistency and asymptotic normality are shown, as well as consistency of an asymptotic variance estimator.
Author: Yanan Fan
Publisher: Academic Press
Published: 2019-10-30
Total Pages: 302
ISBN-13: 0128158638
DOWNLOAD EBOOKFlexible Bayesian Regression Modeling is a step-by-step guide to the Bayesian revolution in regression modeling, for use in advanced econometric and statistical analysis where datasets are characterized by complexity, multiplicity, and large sample sizes, necessitating the need for considerable flexibility in modeling techniques. It reviews three forms of flexibility: methods which provide flexibility in their error distribution; methods which model non-central parts of the distribution (such as quantile regression); and finally models that allow the mean function to be flexible (such as spline models). Each chapter discusses the key aspects of fitting a regression model. R programs accompany the methods. This book is particularly relevant to non-specialist practitioners with intermediate mathematical training seeking to apply Bayesian approaches in economics, biology, finance, engineering and medicine. Introduces powerful new nonparametric Bayesian regression techniques to classically trained practitioners Focuses on approaches offering both superior power and methodological flexibility Supplemented with instructive and relevant R programs within the text Covers linear regression, nonlinear regression and quantile regression techniques Provides diverse disciplinary case studies for correlation and optimization problems drawn from Bayesian analysis ‘in the wild’
Author: Roger W. Klein
Publisher:
Published: 2011
Total Pages:
ISBN-13:
DOWNLOAD EBOOKAuthor: Pravin K. Trivedi
Publisher: Now Publishers Inc
Published: 2007
Total Pages: 126
ISBN-13: 1601980205
DOWNLOAD EBOOKCopula Modeling explores the copula approach for econometrics modeling of joint parametric distributions. Copula Modeling demonstrates that practical implementation and estimation is relatively straightforward despite the complexity of its theoretical foundations. An attractive feature of parametrically specific copulas is that estimation and inference are based on standard maximum likelihood procedures. Thus, copulas can be estimated using desktop econometric software. This offers a substantial advantage of copulas over recently proposed simulation-based approaches to joint modeling. Copulas are useful in a variety of modeling situations including financial markets, actuarial science, and microeconometrics modeling. Copula Modeling provides practitioners and scholars with a useful guide to copula modeling with a focus on estimation and misspecification. The authors cover important theoretical foundations. Throughout, the authors use Monte Carlo experiments and simulations to demonstrate copula properties