Random Coefficient Models for Time-Series-Cross-Section Data: Monte Carlo Experiments

Jonathan N. Katz Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA 91125 e-mail: jkatz{at}caltech.edu e-mail: nathaniel.beck{at}nyu.edu (corresponding author) This article considers random coefficient models (RCMs) fortime-series–cross-section data. These models allow forunit to unit variation in the model parameters. The heart ofthe article compares the finite sample properties of the fullypooled estimator, the unit by unit (unpooled) estimator, andthe (maximum likelihood) RCM estimator. The maximum likelihoodestimator RCM performs well, even where the data were generatedso that the RCM would be problematic. In an appendix, we showthat the most common feasible generalized least squares estimatorof the RCM models is always inferior to the maximum likelihoodestimator, and in smaller samples dramatically so. Authors' note: We gratefully acknowledge the financial supportof the National Science Foundation. Katz also acknowledges thesupport of the Center for Advanced Study in the Behavioral Sciences.We are thankful to Jake Bowers, Rob Franzese, Andy Gelman, SandyGordon, Bill Greene, and Luke Keele for comments; to Larry Bartelsfor always reminding us that our judgment may outperform thedata; as well as to the anonymous reviewers of Political Analysis.     

MMPI-2 and MMPI-2-Restructured Form Validity Scales: Complementary Approaches to Evaluate Response Validity

Responsible forensic assessment is dependent on an appreciation for how validity scales differ from one another and function across different evaluation contexts. The primary goal of this review is to evaluate whether there is sufficient empirical support to provide expert testimony using MMPI-2 or MMPI-2-RF validity scales. Towards this goal, we briefly describe the development of MMPI-2 and MMPI-2-RF validity scales and review empirical studies that support interpretative strategies. We describe and illustrate with case examples how the respective sets of MMPI-2 and MMPI-2-RF validity scales utilize complementary strategies to detect over- and under-reporting of psychological, cognitive, and physical symptoms. Additionally, the review describes standards for expert psychological testimony and illustrates how MMPI-2 and MMPI-2-RF validity scales are particularly well suited to assess symptom validity and psychological status in secondary-gain settings.     

Observing Environmental Destruction Stimulates Neural Activation in Networks Associated with Empathic Responses

The negative impacts of environmental disruption disproportionately affect marginalized and underprivileged communities; thus, the degree to which society is complicit in allowing unchecked environmental destruction to occur has important social justice applications. Although decades of research have sought to understand factors which determine acceptance of environmental destruction, most of this research has been based on self-report surveys. In the present work, we used neuroimaging techniques to examine the neural correlates of environmental concern. To do this, we compared responses to observing suffering dogs with responses to observing suffering ecosystems. Our results extend previous findings which had shown largely overlapping neural response patterns to observing animal and human suffering. Critically, we found activation in regions previously identified as active in empathy processes in response to viewing harm to ecosystems (i.e., without any animals present in the images). We also found relative differences in response patterns between the two types of stimuli: witnessing harm to environments (vs. dog suffering) led to reduced activation in some regions, but similar activation in others. We discuss these findings in terms of their potential implications for behavioral interventions and possibilities for continued neuroimaging research examining neural responses to environmental ecosystems and other nonhuman entities.     

The determinants and interrelationship of carbon emissions and economic growth in African economies: Fresh insights from static and dynamic models

This study explores the interrelationship between CO₂ emissions and economic growth in selected Africa economies from 1990 to 2014 providing evidence from both static and dynamic models. Results show that increases in energy use have a significant and positive effect on economic growth; which goes to show that growth in Africa is actually energy dependent. Further findings suggest that CO₂ emissions have no significant contemporaneous effect, however, a significant and negative effect at a one‐period lag on economic growth. The significance of the impacts is consistently confirmed by both the static and dynamic estimations. Also, trade adds to economic growth and also contributes to environmental deterioration in Africa. There is a dire need for Africa to adjust its energy portfolio by shifting to clean energy sources which will enhance sustainable economic growth without deteriorating the environment.