Most news stories contain both granular quantitative information and coarse categorizations. For instance, company earnings are typically reported as a dollar figure alongside categorizations, such as whether earnings beat or missed market expectations. We study the hypothesis that when a...

Most news stories contain both granular quantitative information and coarse categorizations. For instance, company earnings are typically reported as a dollar figure alongside categorizations, such as whether earnings beat or missed market expectations. We study the hypothesis that when a...

Most news stories contain both granular quantitative information and coarse categorizations. For instance, company earnings are typically reported as a dollar figure alongside categorizations, such as whether earnings beat or missed market expectations. We study the hypothesis that when a...

Most news stories contain both granular quantitative information and coarse categorizations. For instance, company earnings are typically reported as a dollar figure alongside categorizations, such as whether earnings beat or missed market expectations. We study the hypothesis that when a...

Model misspecification in multivariate econometric models can strongly influence estimates of quantities of interest such as structural parameters, forecast distributions or responses to structural shocks, even more so if higher-order forecasts or responses are considered, due to parameter...

Model misspecification in multivariate econometric models can strongly influence estimates of quantities of interest such as structural parameters, forecast distributions or responses to structural shocks, even more so if higher-order forecasts or responses are considered, due to parameter...

AI agents--autonomous systems that perceive, reason, and act on behalf of human principals--are poised to transform digital markets by dramatically reducing transaction costs. This chapter evaluates the economic implications of this transition, adopting a consumer-oriented view of agents as...