Knowledge that Transforms

Do potential entrepreneurs remain in wage employment because of concerns that they will face worse job opportunities should their entrepreneurial ventures fail? Using a Canadian reform that extends job-protected leave to one year for women giving birth after a cutoff date, we study whether the option to return to a previous job increases entrepreneurship. A regression discontinuity design reveals that a longer job-protected leave increases entrepreneurship by 1.9 percentage points. These entrepreneurs start incorporated businesses that hire employees, in industries in which experimentation before entry has low costs and high benefits.

Public pension boards fear inciting stakeholder outrage if they compensate internal investment managers with market-level salaries. We derive theoretical implications in an agency-portfolio-choice model motivated by inequality aversion. In a global sample, relaxing the effect of outrage on contracting leads to an average annual incremental value-added of $49 million generated through 11 bps in higher excess returns from risky assets, at the cost of $302,429 in additional compensation. Governance reforms that address outrage by reducing political appointees or requiring independent skills-based boards can increase the annual value-added. These findings are orthogonal to costly political distortions from underfunding and pay-to-play schemes.

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.

We study the personal credit market using unique individual-level data covering fintech and traditional lenders. We show that fintech lenders acquire market share by lending first to higher-risk borrowers and then to safer borrowers, and rely mainly on hard information to make credit decisions. Fintech borrowers are significantly more likely to default than neighbor individuals with the same characteristics borrowing from traditional financial institutions. Furthermore, they tend to experience a short-lived reduction in the cost of credit, because their indebtedness increases more than non-fintech borrowers after loan origination. However, fintech lenders’ pricing strategies are likely to take this into account.