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 Many consumers do not respond to unanticipated income windfalls, a feature I attribute to adjustment friction in expectations. In the model, consumers incur a fixed cost to adjust cash-on-hand expectations and choose adjustment dates based on noisy signals of expectation error—the difference between actual and expected cash-on-hand. This results in an inattention region where consumers ignore news and do not respond to cash-on-hand changes if the signal remains within the region boundaries. Evidence from expectation and expenditure data supports this departure from Bayesian updating. I investigate implications for the marginal propensity to consume, both qualitatively and quantitatively.

Heterogeneity in individuals' attention to news shapes how aggregate shocks propagate through the economy. We propose a novel method to uncover the full distribution of attention in surveys of consumers and professional forecasters, by developing a finite mixture model to cluster forecasts according to their level of attention. Our results reveal substantial heterogeneity in attention, which, when ignored, leads to an overestimation of average attention. Leveraging our clustering, we construct decade-long panel datasets on attention and provide new insights into its drivers. We document an asymmetric effect of aggregate shocks on the distribution of attention and assess how attention varies with socioeconomic characteristics. Finally, we identify systematic deviations from Bayesian updating and related theories designed to account for behavioral biases. In particular, we find that individuals' attention is less sensitive to changes in uncertainty and signal precision than predicted by these theories. Overall, this paper opens new avenues by providing the first panel datasets on attention and illustrating how they can inform theories of imperfect information through within-individual variations.

Using data from U.S. public companies over recent decades, we document a paradox: while prospective market leaders have gained market share at an increasing speed, overall turnover in leadership has slowed. Although the dynamism of market shares suggests more contestable markets, the persistence of leadership indicates the opposite. We address this puzzle with a model of endogenous growth, where improved consumer access to market data accelerates market share dynamics and increases firms’ incentives to innovate. Greater competition enhances R&D productivity but also amplifies the misallocation of knowledge production. Consequently, innovation occurs through larger but less frequent spikes. Our model aligns with the data, predicting higher market concentration, increased markups, reduced turnover, and slower growth, even alongside more dynamic market shares and higher R&D spending. Ultimately, the paper shifts attention from insufficient competition in the goods market to inefficient competition in the R&D sector as a potential driver of secular fall in aggregate productivity.