FIML Estimation of Sample Selection Models for Count Data
Author | : William H. Greene |
Publisher | : |
Total Pages | : 23 |
Release | : 1997 |
Genre | : |
ISBN | : |
Download FIML Estimation of Sample Selection Models for Count Data Book in PDF, ePub and Kindle
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Fiml Estimation Of Sample Selection Models For Count Data PDF full book. Access full book title Fiml Estimation Of Sample Selection Models For Count Data.
Author | : William H. Greene |
Publisher | : |
Total Pages | : 23 |
Release | : 1997 |
Genre | : |
ISBN | : |
Author | : Rainer Winkelmann |
Publisher | : Springer Science & Business Media |
Total Pages | : 291 |
Release | : 2013-06-29 |
Genre | : Business & Economics |
ISBN | : 3662041499 |
The primary objective of this book is to provide an introduction to the econometric modeling of count data for graduate students and researchers. It should serve anyone whose interest lies either in developing the field fur ther, or in applying existing methods to empirical questions. Much of the material included in this book is not specific to economics, or to quantita tive social sciences more generally, but rather extends to disciplines such as biometrics and technometrics. Applications are as diverse as the number of congressional budget vetoes, the number of children in a household, and the number of mechanical defects in a production line. The unifying theme is a focus on regression models in which a dependent count variable is modeled as a function of independent variables which mayor may not be counts as well. The modeling of count data has come of age. Inclusion of some of the fundamental models in basic textbooks, and implementation on standard computer software programs bear witness to that. Based on the standard Poisson regression model, numerous extensions and alternatives have been developed to address the common challenges faced in empirical modeling (unobserved heterogeneity, selectivity, endogeneity, measurement error, and dependent observations in the context of panel data or multivariate data, to name but a few) as well as the challenges that are specific to count data (e. g. , over dispersion and underdispersion).
Author | : William Greene |
Publisher | : Now Publishers Inc |
Total Pages | : 120 |
Release | : 2007 |
Genre | : Business & Economics |
ISBN | : 160198054X |
This study presents several extensions of the most familiar models for count data, the Poisson and negative binomial models. We develop an encompassing model for two well-known variants of the negative binomial model (the NB1 and NB2 forms). We then analyze some alternative approaches to the standard log gamma model for introducing heterogeneity into the loglinear conditional means for these models. The lognormal model provides a versatile alternative specification that is more flexible (and more natural) than the log gamma form, and provides a platform for several "two part" extensions, including zero inflation, hurdle, and sample selection models. (We briefly present some alternative approaches to modeling heterogeneity.) We also resolve some features in Hausman, Hall and Griliches (1984, Economic models for count data with an application to the patents-R & D relationship, Econometrica 52, 909-938) widely used panel data treatments for the Poisson and negative binomial models that appear to conflict with more familiar models of fixed and random effects. Finally, we consider a bivariate Poisson model that is also based on the lognormal heterogeneity model. Two recent applications have used this model. We suggest that the correlation estimated in their model frameworks is an ambiguous measure of the correlation of the variables of interest, and may substantially overstate it. We conclude with a detailed application of the proposed methods using the data employed in one of the two aforementioned bivariate Poisson studies
Author | : A. Colin Cameron |
Publisher | : Cambridge University Press |
Total Pages | : 597 |
Release | : 2013-05-27 |
Genre | : Business & Economics |
ISBN | : 1107717795 |
Students in both social and natural sciences often seek regression methods to explain the frequency of events, such as visits to a doctor, auto accidents, or new patents awarded. This book, now in its second edition, provides the most comprehensive and up-to-date account of models and methods to interpret such data. The authors combine theory and practice to make sophisticated methods of analysis accessible to researchers and practitioners working with widely different types of data and software in areas such as applied statistics, econometrics, marketing, operations research, actuarial studies, demography, biostatistics and quantitative social sciences. The new material includes new theoretical topics, an updated and expanded treatment of cross-section models, coverage of bootstrap-based and simulation-based inference, expanded treatment of time series, multivariate and panel data, expanded treatment of endogenous regressors, coverage of quantile count regression, and a new chapter on Bayesian methods.
Author | : Adrian Colin Cameron |
Publisher | : Cambridge University Press |
Total Pages | : 597 |
Release | : 2013-05-27 |
Genre | : Business & Economics |
ISBN | : 1107014166 |
This book provides the most comprehensive and up-to-date account of regression methods to explain the frequency of events.
Author | : A. Colin Cameron |
Publisher | : Cambridge University Press |
Total Pages | : 1064 |
Release | : 2005-05-09 |
Genre | : Business & Economics |
ISBN | : 9780521848053 |
The book is oriented to the practitioner.
Author | : Terence C. Mills |
Publisher | : Springer |
Total Pages | : 1406 |
Release | : 2009-06-25 |
Genre | : Business & Economics |
ISBN | : 0230244408 |
Following theseminal Palgrave Handbook of Econometrics: Volume I , this second volume brings together the finestacademicsworking in econometrics today andexploresapplied econometrics, containing contributions onsubjects includinggrowth/development econometrics and applied econometrics and computing.
Author | : Takashi Negishi |
Publisher | : Springer Science & Business Media |
Total Pages | : 542 |
Release | : 2012-12-06 |
Genre | : Business & Economics |
ISBN | : 1461516773 |
Economic Theory, Dynamics, and Markets. The collection of essays in honor of Ryuzo Sato, written by his colleagues and students, covers the many fields of economic theory and policy to which he has contributed. The first section pays tribute to his contributions to mathematical economics and economic theory. Ryuzo Sato is known for his work in growth theory and technical progress, and the second section has a number of papers on macroeconomics and dynamics. The third section has a number of papers on financial markets and their functioning in Japan and the United States. The next section examines various aspects of the economics of firms and industry. Ryuzo Sato has been very involved in analyzing the economic and business relations between Japan and the United States, and the last section is devoted to comparative analysis of economic systems.
Author | : Whitney K. Newey |
Publisher | : |
Total Pages | : 0 |
Release | : 2003 |
Genre | : |
ISBN | : |
Sample 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 | : Azizur Rahman |
Publisher | : Springer Nature |
Total Pages | : 380 |
Release | : 2020-03-31 |
Genre | : Mathematics |
ISBN | : 9811517355 |
This book brings together the best contributions of the Applied Statistics and Policy Analysis Conference 2019. Written by leading international experts in the field of statistics, data science and policy evaluation. This book explores the theme of effective policy methods through the use of big data, accurate estimates and modern computing tools and statistical modelling.