The superiority of full information approaches when estimating a system of equation is well known for large samples. However, less is known about the small sample properties of these estimators … Expand. Highly Influenced. View 4 excerpts, cites methods and background. Threshold effects in the relationship between inflation and growth: a new panel-data approach.
In this paper we use a new approach to throw light on the old question of the super-neutrality of money. Recent theoretical results suggest a threshold model instead of super-neutrality. To ascertain … Expand. Estimation of simultaneous equation models with error components structure. Computer Science, Mathematics. A Survey of Panel Data Models. View 2 excerpts, references methods. I -- Introduction. The author considers the problem of estimation in a panel data sample selection model, where both the selection and the regression equation of interest contain unobservable individual-specific … Expand.
Highly Influential. View 9 excerpts, references background and methods. Pooling: An experimental study of alternative testing and estimation procedures in a two-way error component model. Abstract This paper considers a two-way error component model with no lagged dependent variable and investigates the performance of various testing and estimation procedures applied to this model by … Expand. View 6 excerpts, references background and methods. Multivariate regression models for panel data. Abstract The paper examines the relationship between heterogeneity bias and strict exogeneity in a distributed lag regression of y on x.
The relationship is very strong when x is continuous, weaker … Expand. View 9 excerpts, references results, background and methods.
This paper derives several Lagrange Multiplier tests for the panel data regression model with spatial error correlation. These tests draw upon two strands of earlier work. The first is the LM tests … Expand. View 4 excerpts, references methods and background. It provides both a practical introduction to the subject matter, as well as a thorough discussion of the underlying statistical principles without taxing the reader too greatly.
The book provides several empirical examples that are useful to applied researchers, illustrating them using Stata and EViews showing the reader how to replicate these studies.
It is valuable as a text for a course in panel data, as a supplementary text for more general courses in econometrics, and as a reference. The text has been fully updated with new material on dynamic panel data models, recent results on non-linear panel models, and, in particular, work on limited dependent variables panel data models. Purchasing Power Parity Would you like to change to the site? It is an invaluable read for anyone interested in panel data.
Hausman and Taylor application. Product not available for purchase. It also provides extensionsof panel data techniques to serial correlation, spatialcorrelation, heteroskedasticity, seemingly unrelated regressions, simultaneous equations, dynamic panel models, incomplete panels, measurement error, count panels, rotating panels, limited dependentvariables, and non-stationary panels.
Some Examples 1 1. The datasets are provided on the Wiley web site: Crime in North Carolina 7. You are currently using the site but have requested a page in the site. Table of contents Preface. The exercises start by providing some background information economefric partitioned regressions and the Frisch-Waugh-Lovell theorem. The third edition will also update the panel data literature using newly published papers on dynamic panel data models see chapter 8 and recent results on non-linear panel models and in particular work on limited dependent variables panel data models pamel chapter Featuring the most recent empirical examples from panel data literature, data sets are also provided as well as the programs to implement the estimation and testing procedures described in the book.
View Student Companion Site. Basic Statistical Concepts. Simple Linear Regression. Multiple Regression Analysis. Violations of the Classical Assumptions. Distributed Lags and Dynamic Models. Regression Diagnostics and Specification Tests. Generalized Least Squares. Seemingly Unrelated Regressions. Simultaneous Equations Model.
Limited Dependent Variables. Time-Series Analysis.
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