Although fixed-effects models for panel data are now widely recognized as powerful tools for longitudinal data analysis, the limitations of these models are not well known. We provide a critical discussion of 12 limitations, including a culture of omission, low statistical power, limited external validity, restricted time periods, measurement error, time invariance, undefined variables, unobserved heterogeneity, erroneous causal inferences, imprecise interpretations of coefficients, imprudent comparisons with cross-sectional models, and questionable contributions vis-à-vis previous work. Instead of discouraging the use of fixed-effects models, we encourage more critical applications of this rigorous and promising methodology. The most important deficiencies—Type II errors, biased coefficients and imprecise standard errors, misleading p values, misguided causal claims, and various theoretical concerns—should be weighed against the likely presence of unobserved heterogeneity in other regression models. Ultimately, we must do a better job of communicating the pitfalls of fixed-effects models to our colleagues and students.

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High scientific literacy is widely considered a public good. Methods of assessing public scientific knowledge or literacy are equally important. In an effort to measure lay scientific literacy in the United States, the National Science Foundation (NSF) science literacy scale has been a part of the last three waves of the General Social Survey. However, there has been debate over the validity of some survey items as indicators of science knowledge. While many researchers treat the NSF science scale as measuring a single dimension, previous work (Bann and Schwerin, 2004; Miller, 1998, 2004) suggests a bidimensional structure. This paper hypothesizes and tests a new measurement model for the NSF science knowledge scale and finds that two items about evolution and the big bang are more measures of a religious belief dimension termed "Young Earth Worldview" than they are measures of scientific knowledge. Results are replicated in seven samples.

T his paper considers the history of keywords used in Marketing Science to develop insights on the evolution of marketing science. Several findings emerge. First, "pricing" and "game theory" are the most ubiquitous words. More generally, the three C's and four P's predominate, suggesting that keywords and common practical frameworks align. Various trends exist. Some words, like "pricing," remain popular over time. Others, like "game theory" and "hierarchical Bayes," have become more popular. Finally, some words are superseded by others, like "diffusion" by "social networking." Second, the overall rate of new keyword introductions has increased, but the likelihood they will remain in use has decreased. This suggests a maturation of the discipline or a long-tail effect. Third, a correspondence analysis indicates three distinct eras of marketing modeling, comporting roughly with each of the past three decades. These eras are driven by the emergence of new data and business problems, suggesting a fluid field responsive to practical problems. Fourth, we consider author publication survival rates, which increase up to six papers and then decline, possibly as a result of changes in ability or motivation. Fifth, survival rates vary with the recency and nature of words. We conclude by discussing the implications for additional journal space and the utility of standardized classification codes.

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We advocate a relational approach to understanding contemporary conservatism in the United States. Our approach suggests that conservatism provides a cultural repertoire for adherents to use in adapting to new or changed political situations. We provide evidence based on public opinion data that conservatism is neither a single, monolithic ideology nor a mere coalition of convenience among disparate interest groups. Instead, conservatism should be understood as an amalgam of overlapping but distinct styles of thought, held together through a cultural identification with conservative identity.

Many scholars agree overconsumption is a serious ethical problem because of its adverse effects on the environment. This multimethod article uses two studies to explore the ethical underpinnings of two related consumer expressions of anticonsumption: nonmaterialism, which refers to not placing importance on material goods, and voluntary simplicity, which refers to reducing consumption behavior. Study 1 employs Structural Equation Models of secondary U.S. data and finds that nonmaterialism and voluntary simplicity have unique ethical underpinnings: Nonmaterialism is positively associated with an ethical ideology focused on universal rules and principles while voluntary simplicity is associated with an ethical ideology focused on the consequences of one's actions. Because

M ovie producers and exhibitors make various decisions requiring an understanding of moviegoer's preferences at the local level. Two examples of such decisions are exhibitors' allocation of screens to movies and producers' allocation of advertising across different regions of the country. This study presents a predictive model of local demand for movies with two unique features. First, arguing that consumers' political tendencies have an unutilized predictive power for marketing models, we allow consumers' heterogeneity to depend on their voting tendencies. Second, instead of relying on the commonly used genre classifications to characterize movies, we estimate latent movie attributes. These attributes are not determined a priori by industry professionals but rather reflect consumers' perceptions, as revealed by their moviegoing behavior. Box-office data over five years from 25 counties in the U.S. Midwest provide support for this model. First, consumers' preferences are related to their political tendencies. For example, we find that counties that voted for congressional Republicans prefer movies starring young, Caucasian, female actors over those starring African American, male actors. Second, perceived attributes provide new insights into consumers' preferences. For example, one of these attributes is the movie's degree of seriousness. Finally, and most importantly, the two improvements proposed here have a meaningful impact on forecasting error, decreasing it by 12.6%.