Knowledge that Transforms

To safeguard its technological leadership, the U.S. has restricted domestic suppliers from exporting cutting-edge technologies to selected Chinese firms. Domestic firms affected by these export controls halt sales to Chinese customers, as intended, but struggle to establish new relations with alternative customers domestically or in politically aligned regions. Consequently, domestic suppliers experience sizable losses in market capitalization, along with reductions in profitability, employment, and bank lending. Chinese firms are more proactive in reconfiguring supply chains, though not without costs. Overall, export controls impose larger costs on U.S. firms developing the very technologies these policies aim to protect.

Policy uncertainty can undermine the power of government subsidies to stimulate environmentally friendly research and development. We show that Chinese firms’ green R&D falls as the uncertainty of environmental subsidies rises: Exogenous, weather-driven air pollution variability induces subsidies to fluctuate, and firms in areas with high weather-driven subsidy variability undertake less green R&D and hire fewer technical employees, controlling for the average level of subsidies. Heavy emitters and environmental technology firms are more affected. The results also illustrate how policy uncertainty can arise when policymakers are influenced by conditions that are salient but with causes that are difficult to disentangle.

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.

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 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.