On the effect of prior assumptions in Bayesian model averaging with applications to growth regression

This paper examines the problem of variable selection in linear regression models. Bayesian model averaging has become an important tool in empirical settings with large numbers of potential regressors and relatively limited numbers of observations. The paper analyzes the effect of a variety of prior assumptions on the inference concerning model size, posterior inclusion probabilities of regressors, and predictive performance. The analysis illustrates these issues in the context of cross-country growth regressions using three datasets with 41 to 67 potential drivers of growth and 72 to 93 observations. The results favor particular prior structures for use in this and related contexts.Educational Technology and Distance Education,Geographical Information Systems,Statistical&Mathematical Sciences,Science Education,Scientific Research&Science Parks

Jointness in Bayesian variable selection with applications to growth regression

The authors present a measure of jointness to explore dependence among regressors in the context of Bayesian model selection. The jointness measure they propose equals the posterior odds ratio between those models that include a set of variables and the models that only include proper subsets. They show its application in cross-country growth regressions using two data-sets from the model-averaging growth literature.Statistical&Mathematical Sciences,Climate Change,Educational Technology and Distance Education,Economic Theory&Research,Achieving Shared Growth

Benchmark priors for Bayesian models averaging

In contrast to a posterior analysis given a particular sampling model, posterior model probabilities in the context of model uncertainty are typically rather sensitive to the specification of the prior. In particular, 'diffuse' priors on model-specific parameters can lead to quite unexpected consequences. Here we focus on the practically relevant situation where we need to entertain a (large) number of sampling models and we have (or wish to use) little or no subjective prior information. We aim at providing an 'automatic' or 'benchmark' prior structure that can be used in such cases. We focus on the Normal linear regression model with uncertainty in the choice of regressors. We propose a partly noninformative prior structure related to a Natural Conjugate $g$-prior specification, where the amount of subjective information requested from the user is limited to the choice of a single scalar hyperparameter $g_{0j}$. The consequences of different choices for $g_{0j}$ are examined. We investigate theoretical properties, such as consistency of the implied Bayesian procedure. Links with classical information criteria are provided. In addition, we examine the finite sample implications of several choices of $g_{0j}$ in a simulation study. The use of the MC$^3$ algorithm of Madigan and York (1995), combined with efficient coding in Fortran, makes it feasible to conduct large simulations. In addition to posterior criteria, we shall also compare the predictive performance of different priors. A classic example concerning the economics of crime will also be provided and contrasted with results in the literature. The main findings of the paper will lead us to propose a 'benchmark' prior specification in a linear regression context with model uncertainty.Bayes factors, Markov chain, Monte Carlo, Posterior odds, Prior elicitation

Review: A TEXTBOOK ON LAW AND BUSINESS

A Book Review on A TEXTBOOK ON LAW AND BUSINESS By William H. Spence

Mobilizing Doubt: The Legal Mobilization of Climate Denialist Groups

The climate change counter-movement (CCCM) deploys a broad repertoire of tactics in its effort to cast doubt on the science of climate change. One important yet understudied tactic is the effort by CCCM groups to use open records laws in scientifically uncertain areas to cast doubt on the accuracy of scientific information. This article explores the use of this tactic by CCCM groups and adds to the legal mobilization literature in three ways. First, it traces the origin of CCCM groups to the broader conservative legal movement of the 1970s that challenged the dominance of the liberal legal network. Second, it shows how CCCM groups waged an open records campaign against climate scientists in Virginia and Arizona, which caused a countermobilization by scientists with their own legal campaigns. Finally, this article provides the first empirical evidence of the effect of CCCM FOIA suits on the activities of university researchers. I find, through in-depth personal interviews with twelve university researchers, that the experience of researchers who have been exposed to open records campaigns has been overwhelmingly negative, has caused them to communicate through different media, and has imposed a new work burden that draws them away from other work responsibilities. I argue that the costs of these tactics are narrowly borne by a concentrated group of scientists whose production of knowledge is a public good that allows us to address the crosscutting and relentless problem of climate change

Zu Nachbar. Ein Almanach

Günter Caspar, Sigrid Töpelmann, and Margit Stragies, eds. Berlin and Weimar: Aufbau, 1982. 408 p., 10 M

Margy Gerber, et al., eds.: Studies in GDR Culture and Society 9. Selected Papers from the Fourteenth New Hampshire Symposium on the German Democratic Republic

Lanham: University Press of America, 1989. vii + 210 p

Vested Interests, Venue Shopping, and Policy Stability: The Long Road to Improving Air Quality in Oregon’s Willamette Valley

A lot of scholarly attention has focused on why groups choose to pursue their policy goals in one venue over another. This manuscript adds to the literature by testing a new theory of venue shopping, the Adaptive Venue Shopping Framework. This manuscript finds empirical support that groups choose venues by strategically assessing the institutional context which involves three primary elements: the group\u27s mix of resources, their opponent\u27s resource strengths, and the degree of venue accessibility, which is a combination of opponents degree of control over a venue and a venue\u27s image amiability or receptivity. In addition to confirming these findings, this case study links the literature on venue shopping with recent scholarship about “vested interests” by demonstrating how a powerful agricultural group came to dominate in a legislative venue, how it protected its policy victories from reversal, and how it kept policymaking from shifting into alternative venues, thus leading to long-­‐term policy stability. Furthermore, it demonstrates how newly emerged groups can achieve policy success against stronger opponents by threatening to seek their policy goals in alternative institutions