scholarly journals Random effects dynamic panel models for unequally spaced multivariate categorical repeated measures: an application to child–parent exchanges of support

2020 ◽  
Author(s):  
Fiona Steele ◽  
Emily Grundy
Keyword(s):  
Random Effects ◽  
Repeated Measures ◽  
Dynamic Panel ◽  
Panel Models ◽  
Unequally Spaced ◽  
Dynamic Panel Models ◽  
Multivariate Categorical

Transformed-likelihood estimators for dynamic panel models with a very small T

2020 ◽  
pp. 1-20
Author(s):  
Mark Pickup ◽  
Vincent Hopkins
Keyword(s):  
Panel Data ◽  
Random Effects ◽  
Fixed Effects ◽  
Dynamic Models ◽  
Dynamic Panel ◽  
Panel Models ◽  
Long Run ◽  
Individual Effects ◽  
Lagged Dependent Variable ◽  
Dynamic Panel Models

Conventional OLS fixed-effects and GLS random-effects estimators of dynamic models that control for individual-effects are known to be biased when applied to short panel data (T ≤ 10). GMM estimators are the most used alternative but are known to have drawbacks. Transformed-likelihood estimators are unused in political science. Of these, orthogonal reparameterization estimators are only tangentially referred to in any discipline. We introduce these estimators and test their performance, demonstrating that the unused orthogonal reparameterization estimator in particular performs very well and is an improvement on the commonly used GMM estimators. When T and/or N are small, it provides efficiency gains and overcomes the issues GMM estimators encounter in the estimation of long-run effects when the coefficient on the lagged dependent variable is close to one.

Using Dynamic Panel Models to Study Age–Related Differences and Time–Related Changes in Personality

2019 ◽  
Vol 33 (3) ◽  
pp. 420-434 ◽  
Author(s):  
Jenny Wagner ◽  
Oliver Lüdtke ◽  
Manuel C. Voelkle
Keyword(s):  
Future Research ◽  
Continuous Variables ◽  
Dynamic Panel ◽  
Personality Psychology ◽  
Adult Lifespan ◽  
Panel Models ◽  
Age Related ◽  
Approaches To Study ◽  
Future Research Directions ◽  
Dynamic Panel Models

Along with an increasing interest in the plasticity and role of personality across the adult lifespan comes the need for a diverse set of innovative statistical approaches to study it. With this paper, we set out to illustrate some of the possibilities and challenges in modelling age–related differences and time–related changes in personality psychology by means of dynamic panel models. To this end, we first distinguish between the study of age–related differences and time–related changes and demonstrate how the treatment of age and time as either discrete or continuous variables implies important modelling choices. Second, we present a selection of four example cases that address the topic of age moderation in diverse matters and with different objectives. Based on our cross–tabulation of age and time as discrete and continuous variables, the first two example cases represent fairly well–established models (cases A and B), whereas the remaining cases are used to illustrate current developments in the field (cases C and D). We close the paper with some final remarks on current limitation and future research directions. © 2019 European Association of Personality Psychology

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