We introduce a model that extends the standard vote choice model to encompass text. In our model, votes and speech are generated from a common set of underlying preference parameters. We estimate the parameters with a sparse Gaussian copula factor model that estimates the number of latent dimensions, is robust to outliers, and accounts for zero inflation in the data. To illustrate its workings, we apply our estimator to roll call votes and floor speech from recent sessions of the US Senate. We uncover two stable dimensions: one ideological and the other reflecting to Senators’ leadership roles. We then show how the method can leverage common speech in order to impute missing data, recovering reliable preference estimates for rank-and-file Senators given only leadership votes.

We present a model of political networks that integrates both the choice of trade partners (the extensive margin) and trade volumes (the intensive margin). Our model predicts that regimes secure in their survival, including democracies as well as some consolidated authoritarian regimes, will trade more on the extensive margin than vulnerable autocracies, which will block trade in products that would expand interpersonal contact among their citizens. We apply a two-stage Bayesian LASSO estimator to detailed measures of institutional features and highly disaggregated product-level trade data encompassing 131 countries over a half century. Consistent with our model, we find that (a) political institutions matter for the extensive margin of trade but not for the intensive margin and (b) the effects of political institutions on the extensive margin of trade vary across products, falling most heavily on those goods that involve extensive interpersonal contact.

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