In the months before the 2020 U.S. election, several political campaign websites added prechecked boxes (defaults), automatically making all donations into recurring weekly contributions unless donors unchecked them. Since these changes occurred at different times for different campaigns, we use a staggered difference-in-differences design to measure the causal effects of defaults on donors’ behavior. We estimate that defaults increased campaign donations by over $43 million while increasing requested refunds by almost $3 million.
How can firms encourage consumers to adopt smartphone apps? The authors show that several inexpensive choice architecture techniques can make users more likely to enable important app features and complete app onboarding. In six preregistered experiments (n = 5,968) and a field experiment (n = 594,997), choice architecture interventions manipulating choice sequence, color, and wording of app adoption decisions dramatically increased app adoption. Across experiments, integrating multiple feature decisions into a single choice increased adoption.
How can we measure the extent to which data-intensive firms are using their market power? Economists typically look to markups as evidence of market power. Using a simple model with firms that price risk in their capital allocation and production decisions, we highlight the competing forces that make markups an unreliable measure of data-derived market power. Instead, we show how markups measured at different levels of aggregation reflect data and distinguish data from other intangible investments.
We develop a novel technique to extract credit-relevant information from the text of quarterly earnings calls. This information is not spanned by fundamental or market variables and forecasts future credit spread changes. One reason for such forecastability is that our text-based measure predicts future credit spread risk and firm profitability. More firm- and call-level complexity increase the forecasting power of our measure for spread changes. Out-of-sample portfolio tests show the information in our measure is valuable for investors.
Gamified training is a novel management control system in which companies use gamification techniques to engage and motivate employees to learn. This study empirically examines the performance consequences of gamified training using data from a natural field experiment in a professional services firm. We find that, on average, the main effect of adopting the gamified training platform on performance is significantly positive. We also study whether outcomes depend on how engaged the office is in the gamified training platform (i.e.
Standard search models assume that consumers actively decide on the order, identity, and number of products they search. We document that online, a large fraction of searches happen in a more passive manner, with consumers merely reacting to online advertisements that do not allow them to choose the timing or the identity of products to which they will be exposed. Using a clickstream panel data set capturing full URL addresses of websites consumers visit, we show how to detect whether a click is ad-initiated.
Equity investors have been shifting away from actively managed funds to passive strategies for decades. Passification, if that is a word, has been slower to take off in fixed-income strategies, though.
Agile decision making is imperative as you lead in a data-driven world. Uniquely bridging theory and practice, Decisions over Decimals unites data intelligence with human judgment to get to action – a sharp approach the authors refer to as Quantitative Intuition (QI). QI raises the power of thinking beyond big data without neglecting it and chasing the perfect decision while appreciating that such a thing can never really exist.