Knowledge that Transforms

Using transaction level data from the inter-dealer market, we find that the price impact of one standard deviation change in FX swap order flow has increased from less than one basis point prior to 2008 to about five basis points after 2008. However, the increase in price impact is confined to periods of elevated dispersion in funding costs and over quarterends. Central bank swap lines reduce the order flow into USD, subsequently affecting the FX forward rate. In contrast, over quarter-ends and after monetary policy announcements we observe that dealers immediately adjust prices to curb order flow.

Using the introduction of high-speed rail (HSR) as an exogenous shock to costs of information acquisition, we show reductions in information-acquisition costs lead to (i) a significant increase in information production, evidenced by a higher frequency of analysts visiting portfolio firms and (ii) improvement in output quality, manifested in higher forecast accuracy and better recommendations. The effect is more pronounced for firms with information that is difficult to produce. Importantly, more information production is also associated with improved price efficiency. We corroborate these findings using a large-scale survey of financial analysts. Finally, both the empirical and survey results highlight the importance of soft information in analysts’ unique-information production.

Firms sharing a board member with a media company receive more news coverage. This in turn affects those firms’ financing choices: they issue more bonds, rely less on bank loans, and have lower blockholder ownership. These findings are consistent with media coverage acting as an external governance mechanism that substitutes for monitoring by banks and equity blockholders. The effect of media-linked directors on financing is evident in panel and time series analyses and using two different instrumental variable analyses, suggesting a causal relation.

Using data on 50 million home sales from the last U.S. housing cycle, we document that much of the variation in volume came from the rise and fall in speculation. Cities with larger speculative booms have larger price booms, sharper increases in unsold listings as the market turns, and more severe busts. We present a model in which predictable price increases endogenously attract short-term buyers more than long-term buyers. Short-term buyers amplify volume by selling faster and destabilize prices through positive feedback. Our model matches key aggregate patterns, including the lead–lag price–volume relation and a sharp rise in inventories.

We propose a new explanation for the persistence of gravity in international investment flows based on new facts about large cross-border commercial real estate transactions. Buyers in these transactions preferentially match with counterparties from own or proximate countries; such affinity-based matching helps alleviate financial investment frictions. We set up and structurally estimate a model of capital allocation in a decentralized market with an investment friction, which delivers the price, volume, and counterparty matching patterns in the data. The model shows that if clusters of high-affinity counterparties lie along historical routes, as in the data, preferential matching can perpetuate gravity relationships.

What are the economic determinants of a firm’s market value? We answer this question through the lens of a generalized neoclassical model of investment with quasi-fixed labor and three heterogeneous capital inputs. We estimate the structural model using firm-level data on US firms and find that, on average and depending on the industry, installed labor force accounts for 14–21% of firms’ market value, physical capital accounts for 30–40%, knowledge capital accounts for 20–43%, and brand capital accounts for 6–25%. Our analysis provides direct empirical evidence for the importance of labor and intangible capital inputs for understanding firm value.

We evaluate the impact of the Federal Reserve corporate credit facilities (PMCCF and SMCCF) on corporate bond markets. Conditions in primary markets improve once the facilities are announced, particularly for issuers that need to refinance before 2022. Issuance accelerates before spreads normalize. The secondary market points to a causal role for the facilities, with a differential impact on eligible issues and a significant effect of direct bond purchases, but less so for purchases through ETFs. We find evidence that dealers link the primary and secondary market recovery, with facilities affecting dealer willing to underwrite issuances and intermediate in secondary markets.

We document that networks that gain access to political power and use it for patronage appointments also gain control over resource allocation in the private sector. Specifically, following a presidential election in Korea, the president appoints members of his network into important positions in government, and private banks respond by appointing executives from the same network to establish links to the administration. Consequently, firms linked to the network obtain more credit at a lower rate from government and private banks alike, despite higher default rates. Micro-level data on loans and variation in network links for the same firm across lenders over time sharpen the interpretation of our results. In a parsimonious model, we show that efficiency costs are higher when government and private banks are controlled by the same group rather than different groups: in-group firms invest in more unprofitable projects, whereas out-group firms lack funding for highly profitable investments.

This paper studies manipulation in derivative contract markets. When traders hedge factor risk using derivative contracts, traders can manipulate settlement prices by trading the underlying spot goods. In equilibrium, manipulation can make all agents worse off. The model illustrates how contract market manipulation can be defined in a manner distinct from other forms of strategic trading behavior, and how the structure of contract and spot markets affect the size of manipulation-induced market distortions.

Landlords appear to use stale information when setting rents. Among over 43,000 California rental houses in 2018–2019, those last purchased during 2005–2007 (the peak) rent for 2–3% more than those purchased during 2008–2010 (bust). Neither house nor landlord characteristics explain this “peak-bust rental spread.” To clarify the mechanism, we test cross-sectional predictions from a simple theory of rent-setting. We find empirical support for both reference dependence and distorted beliefs. In the first, monthly payments establish (recurring) reference points, against which gains or losses are measured. In the second, past sales prices distort landlords’ current estimates of house values/rents.