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AbstractThe papers in this symposium use Monte Carlo simulations to demonstrate the consequences of estimating time series models with variables that are of different orders of integration. In this summary, I do the following: very briefly outline what we learn from the papers; identify an apparent contradiction that might increase, rather than decrease, confusion around the concept of a balanced time series model; suggest a resolution; and identify a few areas of research that could further increase our understanding of how variables with different dynamics might be combined. In doing these things, I suggest there is still a lack of clarity around how a research practitioner demonstrates balance, and demonstrates what Pickup and Kellstedt (2021) call I(0) balance.

Abstract.Using time series, cross-sectional econometric modelling, an analysis is made of competing political and economic determinants of Canadian provincial government fiscal policy during the 1980s and 1990s. It is determined that provincial government spending responses to trade liberalization are dependent upon the ideology of the government and conditioned by the degree of provincial unionization. When relatively high levels of unionization prevail, those governments that typically spend the most reduce total spending to a lowest common denominator. However, when unionization is low, provincial government spending responses to increasing trade openness is primarily compensatory. This is in contradiction to the "race to the bottom" theory. The contingent nature of the provincial government spending response to trade openness means that despite overall pressures for fiscal convergence, political, economic and regional factors continue to contribute to distinct provincial spending policies.Résumé.Cet article utilise une modélisation économétrique transversale en série chronologique pour analyser les déterminants politiques et économiques en compétition au niveau de la politique fiscale du gouvernement provincial canadien durant les années 1980 et 1990. Il est établi qu'en termes de dépenses publiques, les réactions du gouvernement provincial face à la libéralisation des échanges sont tributaires de l'idéologie du gouvernement et déterminées par le niveau de syndicalisation provincial. Lorsque le niveau de syndicalisation est relativement élevé, ce sont les gouvernements provinciaux qui dépensent le plus qui réduisent leurs dépenses totales au plus bas dénominateur commun. Par contre, plus le niveau de syndicalisation est bas, plus les dépenses publiques face à la libéralisation des échanges sont principalement compensatoires. Cela vient contredire la théorie du " nivellement par le bas ". La nature conditionnelle de la réaction du gouvernement provincial en termes de dépenses publiques signifie qu'en dépit des pressions globales pour la convergence fiscale, des facteurs politiques, économiques et régionaux continuent de contribuer aux politiques de dépenses publiques distinctes.

The underlying motivation of this collection is the concern that the failure to understand the relationship between our measure of a concept and the concept itself has real consequences. It may cause us to overlook model specification problems, to unnecessarily and inappropriately change our theories, and to miss out on information that could be usefully applied to the specification and estimation of our model. In order to take modelling seriously, we first must take measurement seriously. This is most effectively done when multiple measures of the underlying concept are utilised, allowing for the application of more appropriate models with more precise estimates. The contributions to this symposium demonstrate a wide range of such modelling approaches, each of which is tailored to match the theoretical expectations for the statistical characteristics of the data being used. By way of introduction, I highlight the measurement problems that these approaches are designed to tackle. [Copyright Elsevier Ltd.]

A growing number of Americans stay informed about current events through social media. But using social media as a source of news is associated with increased likelihood of being misinformed about important topics, such as COVID-19. The two most popular platforms—Facebook and YouTube—remain relatively understudied in comparison to Twitter, which tends to be used by elites, but less than a quarter of the American public. In this brief research report, we investigate how cognitive reflection can mitigate the potential effects of using Facebook, YouTube and Twitter for news on subsequent conspiracy theory endorsement. To do that, we rely on an original dataset of 1,009 survey responses collected during the first wave of the coronavirus pandemic in the United States, on March 31, 2020. We find that using Facebook and YouTube for news increases conspiracy belief (both general and COVID-19 specific), controlling for cognitive reflection, traditional news media use, use of web-based news media, partisanship, education, age, and income. We also find that the impact of Facebook use on conspiracy belief is moderated by cognitive reflection. Facebook use increases conspiracy belief among those with low cognitive reflection but has no effect among those with moderate levels of cognitive reflection. It might even decrease conspiracy belief among those with the highest levels of cognitive reflection.

Research examining attitudes and behaviors of Americans during the COVID-19 pandemic has largely focused on partisanship as a lens through which many Americans see the coronavirus. Given the importance of partisan affiliation and the degree of partisan polarization in the American society, that is certainly an important driver of public opinion, and a necessary one to understand. But an overlooked set of predispositions might also shape COVID beliefs and attitudes: populism. It is a worldview that pits average citizens against "the elites" and, importantly in the context of a pandemic, it includes anti-intellectual attitudes such as distrust of experts (including scientists). We find that populism is correlated with conspiracy beliefs about COVID-19, above and beyond partisanship. Furthermore, we find that conservative media consumption tends to be a stronger predictor of conspiracy belief among those high in populism than among those low in populism. We also show that these beliefs have consequences: those who believe the conspiracy theories about COVID-19 are less likely to adapt behaviors recommended by public health officials.

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.