We study how U.S. dollar fluctuations transmit through domestic supply chains in emerging markets. Large firms borrow in foreign currency and extend trade credit to domestic partners, exposing the supply chain to exchange rate risk. We develop a model where financially constrained suppliers pass through shocks to buyers, while unconstrained firms absorb them. Using quarterly firm-level data from 19 emerging markets, we provide empirical evidence consistent with the model’s predictions. We find that even highly exposed firms reduce trade credit only modestly following a depreciation, while accepting large profit losses, suggesting that firm-to-firm credit relationships partially shield downstream firms from financial shocks.

Using mutual fund flows, we evaluate prospect theory with choice outcomes in the market. We provide strong support for prospect theory: under a standard set of parameters, funds whose past returns generate higher prospect theory value attract significantly larger future flows; we also find corroborative evidence using account-level data. Taking a revealed preference approach, we estimate the prospect theory parameters through a discrete choice model and find that our field-based estimates align well with previous experiment-based estimates. Moreover, we show that prospect theory offers a new framework for understanding flows, as it has explanatory power beyond existing drivers.

We study the nature and effects of cultural biases in choice under risk and uncertainty by comparing peer-to-peer loans the same individuals ( lenders ) make alone and after observing robo-advised suggestions. When unassisted, lenders are more likely to choose co-ethnic borrowers, facing 8% higher defaults and 7.3pp lower returns. Robo-advising does not affect diversification but reduces lending to high-risk co-ethnic borrowers. Lenders in locations with high inter-ethnic animus drive the results, even when borrowers reside elsewhere. Biased beliefs explain these results better than a conscious taste for discrimination: lenders rarely override robo-advised matches to ethnicities they discriminated against when unassisted.

We document implicit extrapolation in investment decision-making that exceeds the extrapolation inferable from stated expectations. Locally experienced returns predict individual real-estate investment decisions even conditional on an investor’s forecasted home-price growth and risk aversion. Moreover, estimates of this experience effect on investment are larger than implied by the combined effect of past returns on stated expectations and stated expectations on investment. We demonstrate that heterogeneous forecast confidence helps explain why many investors rely on past returns over their survey-elicited forecasts. As their rationale, such survey respondents frequently cite intentional extrapolation or a lack of confidence in other belief factors.

Disagreement about macroeconomic fundamentals accounts for only part of the disagreement about future interest rates, creating a “disagreement correlation” puzzle. This puzzle arises because standard equilibrium models with belief differences predict a strong link between asset return disagreement and fundamental disagreement, a link not supported by the data. We address this puzzle by introducing a model where disagreement about future demand for savings—driven by disagreement over the prevalence of patient versus impatient investors in the economy—generates asset return disagreement. Our mechanism produces stochastic yield volatility, time-varying bond risk premia, and an upward-sloping yield curve. Empirically, we construct a proxy for demand disagreement by isolating the component of yield disagreement unrelated to disagreement about macro-fundamentals. This proxy is positively related to yields and their volatilities, and predicts future bond risk premia, consistent with the predictions of our demand disagreement model.

This paper studies the transmission of monetary policy to the stock market through investors’ discount factors. To isolate this channel, we investigate the effect of US monetary policy surprises on the ratio of prices of the same stock listed simultaneously in Hong Kong and Mainland China. We identify a strong discount rate channel driven exclusively by cycle-amplifying surprises, defined as rate cuts during easing cycles and surprise hikes during tightening cycles. A 100 basis point of such cycle-amplifying surprise induces a 30 basis point change in the price ratio within five days

We test whether forecast bias affects household stock trading by combining measures of bias elicited in laboratory experiments with administrative trade-level data. On average, subjects exhibit positive forecast bias (i.e., extrapolators), while a large minority exhibit negative forecast bias (i.e., contrarians). Forecast bias is positively associated with past excess returns of stocks that are purchased: Extrapolators (contrarians) purchase past winners (losers). Forecast bias is negatively associated with the capital gains of stocks that are sold. Furthermore, forecast bias explains investor heterogeneity in the relation between market returns and net flows to stocks. Overall, our study provides evidence of a common mechanism – forecast bias – that links past returns to trading decisions for purchases, sales, and net flows.