The purpose of this paper is to determine whether the information content in the consumer confidence index explains demand in Pakistan, beyond economic fundamentals. We use a wide range of models, starting from ordinary least squares to linear regression models that incorporate common factors driven by principal components, as well as advanced machine learning techniques, including penalized regression methods and neural networks. We apply both fixed and expanding window rolling forecasts to test this phenomenon and present our results using three forecast accuracy measures. Overall, our findings demonstrate that, for each technique considered, the model that includes the consumer confidence information set outperforms the model based solely on economic fundamentals. This indicates that the information content of consumer confidence enhances the explanation of demand-side indicators in Pakistan. This paper directly informs policymakers in developing countries generally, and in Pakistan specifically, that the consumer confidence index offers insights into the expectations of economic agents and should be integrated into analyses for improved policy decisions.