Knowledge that Transforms

Credit supply expansion boosts housing speculation and amplifies the housing cycle. The surge in private-label mortgage securitization in 2003 fueled a large expansion in mortgage credit supply by lenders financed with noncore deposits. Areas more exposed to these lenders experienced a large relative rise in transaction volume driven by a small group of speculators, and these areas simultaneously witnessed an amplified housing boom and bust. Consistent with the importance of belief heterogeneity, house price growth expectations of marginal buyers rose during the boom, while housing market pessimism among the general population increased.

To understand what motivates individuals to look at their pension situation and make adequate savings decisions, we conduct two field experiments with 226,946 and 257,433 pension fund participants. We find peer-information statements do not increase the rate at which individuals check their pension information, but lottery-type financial incentives do. Offering a few large prizes rather than many small prizes is most effective. However, the uptake of pension information does not lead to improved pension knowledge nor to increased self-reported savings three weeks after our intervention.

Binding lower bounds on interest rates and large government deficits limit the scope of fiscal and monetary policies to stimulate households’ spending through financial intermediaries and firms. Policy makers have thus been implementing unconventional policies that aim to increase households’ spending directly through managing their expectations. We first show theoretically and empirically that higher inflation expectations increase households’ consumption. We then design a difference-in-differences strategy to assess the effectiveness of unconventional fiscal policy and forward guidance, both of which aim to raise aggregate demand via managing expectations. Whereas unconventional fiscal policy increases households’ expectations and spending, forward guidance announcements do not

To understand deviations from covered interest parity (CIP), it is crucial to account for heterogeneity in funding costs across both banks and currency areas. For most market participants, the no-arbitrage relation holds fairly well when implemented using marginal funding costs and risk-free investment instruments. However, a few high-rated banks do enjoy CIP-arbitrage opportunities. Dealers avert inventory imbalances stemming from lower-rated banks’ usage of FX swaps to obtain dollar funding by inducing opposite (arbitrage) flows from high-rated banks. Arbitrage trades are difficult to scale, however, because funding costs increase as soon as arbitrageurs increase positions.

We apply a machine-learning algorithm, calibrated using general human vision, to predict the visual salience of prices of stock price charts. We hypothesize that the visual salience of adjacent prices increases the decision weights on returns computed from those prices. We analyze the inferred impact of these weights in two experimental studies that use either historical price charts or simpler artificial sequences. We find that decision weights derived from visual salience are associated with experimental investments. The predictability is not subsumed by statistical features and goes beyond established models.

Since the finance industry is transforming into a data industry, measuring the quantity of data investors have about various assets is important. Informed by a structural model, we develop such a cross-sectional measure. We show how our measure differs from price informativeness and use it to document a new fact: data about large high-growth firms is becoming increasingly abundant, relative to data about other firms. Our structural model offers an explanation for this data divergence: large high-growth firms’ data became more valuable, as big firms got bigger and growth magnified the effect of these changes in size.

The proportion of U.K. people with university degrees tripled between 1993 and 2015. However, over the same period the time trend in the college wage premium has been extraordinarily flat. We show that these patterns cannot be explained by composition changes. Instead, we present a model in which firms choose between centralized and decentralized organizational forms and demonstrate that it can explain the main patterns. We also show the model has implications that differentiate it from both the exogenous skill-biased technological change model and the endogenous invention model, and that U.K. data fit with those implications. The result is a consistent picture of the transformation of the U.K. labour market in the last two decades.

Many studies use shift-share (or "Bartik") instruments, which average a set of shocks with exposure share weights. We provide a new econometric framework for shift-share instrumental variable (SSIV) regressions in which identification follows from the quasi-random assignment of shocks, while exposure shares are allowed to be endogenous. The framework is motivated by an equivalence result: the orthogonality between a shift-share instrument and an unobserved residual can be represented as the orthogonality between the underlying shocks and a shock-level unobservable. SSIV regression coefficients can similarly be obtained from an equivalent shock-level regression, motivating shock-level conditions for their consistency. We discuss and illustrate several practical insights of this framework in the setting of Autor et al. (2013), estimating the effect of Chinese import competition on manufacturing employment across U.S. commuting zones.

Unemployment insurance (UI) programs traditionally take the form of a single insurance contract offered to job seekers. In this work, we show that offering a menu of contracts can be welfare improving in the presence of adverse selection and moral hazard. When insurance contracts are composed of (1) a UI payment and (2) a severance payment paid at the onset of unemployment, offering contracts with different ratios of UI benefits to severance payment is optimal under the equivalent of a single-crossing condition: job seekers in higher need of unemployment insurance should be less prone to moral hazard. In that setting, a menu allows the planner to attract job seekers with a high need for insurance in a contract with generous UI benefits, and to attract job seekers most prone to moral hazard in a separate contract with a large severance payment but little unemployment insurance. We propose a simple sufficient statistics approach to test the single-crossing condition in the data.

We investigate the allegation that legacy US airlines communicated via earnings calls to coordinate with other legacy airlines in offering fewer seats on competitive routes. To this end, we first use text analytics to build a novel dataset on communication among airlines about their capacity choices. Estimates from our preferred specification show that the number of offered seats is 2% lower when all legacy airlines in a market discuss the concept of “capacity discipline.” We verify that this reduction materializes only when legacy airlines communicate concurrently, and that it cannot be explained by other possibilities, including that airlines are simply announcing to investors their unilateral plans to reduce capacity, and then following through on those announcements.