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Political scientists often find themselves analyzing data sets with a large number of observations, a large number of variables, or both. Yet, traditional statistical techniques fail to take full advantage of the opportunities inherent in “big data,” as they are too rigid to recover nonlinearities and do not facilitate the easy exploration of interactions in high‐dimensional data sets. In this article, we introduce a family of tree‐based nonparametric techniques that may, in some circumstances, be more appropriate than traditional methods for confronting these data challenges. In particular, tree models are very effective for detecting nonlinearities and interactions, even in data sets with many (potentially irrelevant) covariates. We introduce the basic logic of tree‐based models, provide an overview of the most prominent methods in the literature, and conduct three analyses that illustrate how the methods can be implemented while highlighting both their advantages and limitations.

Even though climate scientists are nearly unanimous that climate change is real and manmade, about 40% of Americans reject the scientific consensus. Why? The largest contributing factor is partisanship; however, recent studies argue that underlying conspiracy thinking exerts a positive, linear effect on climate change denial. In this article, we reexamine the effect of conspiracy thinking on climate change attitudes by accounting for the various pathways that conspiracy thinking could drive denialism in a politically polarized environment. We find the effects of conspiracy thinking on climate change denial are not only larger than previously suggested, but also non-monotonic and conditional on individuals' party identification. Moreover, we find evidence suggesting conspiracy thinking affects independents' positions, and even their partisan leanings. These findings further explain why people reject the scientific consensus on climate change, and suggest that climate change denial is not merely the product of partisan polarization.

Data has been taken from the Hungarian National Assembly, where the mandate type (single member district (SMD) vs. party list or proportional representation (PR)) changes for a number of legislators each term, to explore whether and how such changes lead to changes in legislators' voting behavior. When the electoral system under which a legislator was elected changes from PR to SMD, then the rate at which the legislator defects against the party line of voting increases significantly. Contrary to expectations, when the electoral system changes from SMD to PR, there is no significant change in the voting behavior of legislators. Additional robustness tests confirm these results. The lasting influence of reputations and habits may account for the asymmetric results. * Washington University in St. Louis (emails: olivella@wustl.edu, tavits@wustl.edu). We would like to thank Thames 2005. Another possibility is to compare different legislative chambers in the same country if these chambers employ different electoral rules (see, for example, Desposato 2006). However, these situations are rare, and, therefore, MMS has become a more commonly used setting for studying the causal connection at hand.