Since the seminal work of Stigler in 1962, economists have recognized that information is costly to acquire and leads to “search frictions.” Growth in online search has lowered the cost of information acquisition. We analyze the expansion of the website Craigslist, which allows users to post job and housing ads. Exploiting the sharp geographic and temporal variation in the availability of online search induced by Craigslist, we produce three key findings: Craigslist significantly lowered classified job advertisements in newspapers, caused a significant reduction in the apartment and house rental vacancy rate, and had no effect on the unemployment rate.

Although experimental studies have documented systematic decision errors, many leading scholars believe that experience, competition, and large stakes will reliably extinguish biases. We test for the presence of a fundamental bias, loss aversion, in a high-stakes context: professional golfers' performance on the PGA Tour. Golf provides a natural setting to test for loss aversion because golfers are rewarded for the total number of strokes they take during a tournament, yet each individual hole has a salient reference point, par. We analyze over 2.5 million putts using precise laser measurements and find evidence that even the best golfers—including Tiger Woods—show evidence of loss aversion. (JEL D03, D81, L83).

Households that fail to refinance their mortgage when interest rates decline lose out on substantial savings. Using a random sample of outstanding US mortgages in December 2010, we estimate that approximately 20% of unconstrained households for whom refinancing was optimal had not done so. The median household would save $160/month over the remaining life of the loan, for a total present-discounted value of forgone savings of $11,500, a particularly large consumer financial mistake. To shed light on possible mechanisms, we also provide results from a mail campaign targeted at a sample of homeowners who could benefit from refinancing.

When judging the value of a good, people may be overly influenced by the state in which they previously consumed it. For example, someone who tries out a new restaurant while very hungry may subsequently rate it as high quality, even if the food is mediocre. We produce a simple framework for this form of attribution bias that embeds a standard model of decision making as a special case. We test for attribution bias across two consumer decisions. First, we conduct an experiment in which we randomly manipulate the thirst of participants prior to consuming a new drink. Second, using data from thousands of amusement park visitors, we explore how pleasant weather during their most recent trip affects their stated and actual likelihood of returning. In both of these domains, we find evidence that people misattribute the influence of a temporary state to a stable quality of the consumption good. We provide evidence against several alternative accounts for our findings and discuss the broader implications of attribution bias in economic decision making.

Can heuristic information processing affect important product markets? Analyzing over 22 million wholesale used-car transactions, we find evidence of left-digit bias in the processing of odometer values, whereby individuals focus on the number's leftmost digits. The bias leads to discontinuous drops in sale prices at 10,000-mile odometer thresholds, along with smaller drops at 1,000-mile thresholds. These findings reveal that information-processing heuristics matter even in markets with large stakes and easily observed information. We model left-digit bias in an inattention framework and structurally estimate the inattention parameter. Empirical patterns suggest the results are driven by final customers rather than professional agents. (JEL D12, D44, D83, L81)

We study inaccurate beliefs as a source of discrimination. Economists typically characterize discrimination as stemming from a taste-based (preference) or accurate statistical (belief-based) source. Although individuals may have inaccurate beliefs about how relevant characteristics (e.g., productivity, signals) are correlated with group identity, fewer than 7% of empirical discrimination papers in economics consider the possibility of such inaccurate statistical discrimination. Using theory and a labor market experiment, we show that failing to account for inaccurate beliefs leads to a misclassification of source. We outline three methods to identify source: varying observed signals, belief elicitation, and an intervention to target inaccurate beliefs.

Equal access to voting is a core feature of democratic government. Using data from hundreds of thousands of smartphone users, we quantify a racial disparity in voting wait times across a nationwide sample of polling places during the 2016 U.S. presidential election. Relative to entirely white neighborhoods, residents of entirely black neighborhoods waited 29% longer to vote and were 74% more likely to spend more than thirty minutes at their polling place. This disparity holds when comparing predominantly white and black polling places within the same states and counties and survives numerous robustness and placebo tests. We shed light on the mechanism for these results and discuss how geospatial data can be an effective tool to measure and monitor these disparities going forward.

When judging the value of a good, people may be overly influenced by the state in which they previously consumed it. For example, someone who tries out a new restaurant while very hungry may subsequently rate it as high quality, even if the food is mediocre. We produce a simple framework for this form of attribution bias that embeds a standard model of decision making as a special case. We test for attribution bias across two consumer decisions. First, we conduct an experiment in which we randomly manipulate the thirst of participants prior to consuming a new drink. Second, using data from thousands of amusement park visitors, we explore how pleasant weather during their most recent trip affects their stated and actual likelihood of returning. In both of these domains, we find evidence that people misattribute the influence of a temporary state to a stable quality of the consumption good. We provide evidence against several alternative accounts for our findings and discuss the broader implications of attribution bias in economic decision making.

When buying durable goods, consumers must forecast how much utility they will derive from future consumption, including consumption in different states of the world. This can be complicated for consumers because making intertemporal evaluations may expose them to a variety of psychological biases such as present bias, projection bias, and salience effects. We investigate whether consumers are affected by such intertemporal biases when they purchase automobiles. Using data for more than 40 million vehicle transactions, we explore the impact of weather on purchasing decisions. We find that the choice to purchase a convertible or a four-wheel-drive is highly dependent on the weather at the time of purchase in a way that is inconsistent with classical utility theory. We consider a range of rational explanations for the empirical effects we find, but none can explain fully the effects we estimate. We then discuss and explore projection bias and salience as two primary psychological mechanisms that are consistent with our results.

We investigate whether the first digit of an odometer reading is more salient to consumers than subsequent digits. We find that retail transaction prices and volumes of used vehicles drop discontinuously at 10,000-mile odometer thresholds, echoing effects found in the wholesale market by Lacetera, Pope and Sydnor (2012). Our results reveal that retail consumers devote limited attention to evaluating vehicle mileage, and that this drives effects in the wholesale market. We estimate the inattention parameter implied by the price discontinuities. In addition, our results suggest that estimating consumer-level structural parameters using data from an intermediate market can give misleading results.