Abstract: Algorithmic pricing can improve efficiency by helping firms set prices more responsive to changing market conditions. However, widespread adoption of the same algorithm could also lead to price coordination, resulting in elevated prices. In this paper, we examine the impact of algorithmic pricing on the U.S. multifamily rental housing market using hand-collected adoption decisions of property management companies merged with the data of market-rate multifamily apartments from 2005 to 2019. First, our findings suggest that algorithm adoption indeed helps building managers set more responsive prices: buildings with the software increase prices during booms and lower prices during busts, compared to non-adopters in the same market. Second, when compared across markets, we find markets with greater algorithm penetration also experienced higher rents and lower occupancy in the post-crisis period. Such empirical patterns are consistent with either price coordination through the algorithm or widespread pricing error among non-adopters. Lastly, we estimate a structural model of housing demand and perform a test of conduct to evaluate the "algorithmic coordination" hypothesis.
Abstract: I quantify the contribution of intermediary agency frictions to the cyclicality of lending
by collateralized loan obligations (CLOs). CLOs’ cost of debt contains significant
compensation for agency problems arising from CLOs’ discretion in trading. Agency
problems intensify in volatile periods, raising CLOs’ cost of debt, reducing the issuance
of new CLOs, and affecting real outcomes in CLO-dependent firms. To mitigate this
effect, CLOs issued in volatile periods restrict their discretion, which, however, also
limits valuable trading. Using a structural model, I estimate that one third of the
steep fall in CLO issuance during volatile periods is due to agency frictions.
Discussant: Wenhao Li, University of Southern California
Abstract: We estimate the impact of household liquidity provision on macroeconomic stabilization using the 2020 CARES Act mortgage forbearance program. We leverage intermediation frictions in forbearance induced by mortgage servicers to identify the effect of reducing short-term payments with little change in long-term debt obligations on local labor market outcomes. Following statewide business reopenings, a one percentage point increase in the share of mortgages in forbearance leads to a 30 basis point increase in monthly employment growth in nontradable industries. In a model incorporating geographical heterogeneity in intermediation frictions, these responses imply a household-level marginal propensity to consume out of increased liquidity that aligns with existing estimates for direct fiscal transfers. The implied debt-financed fiscal multiplier effects of forbearance are sizable but depend on the repayment terms of deferred payments and the monetary policy stance.
Discussant: Jacelly Cespedes, University of Minnesota
Pascal Paul, Federal Reserve Bank of San Francisco
Abstract: We study the transmission of monetary policy through bank securities portfolios for the United States using granular supervisory data on bank securities, hedging positions, and corporate credit. We find that banks that experienced larger market value losses on their securities during the monetary tightening cycle in 2022 extended relatively less credit to firms. Such a spillover effect was stronger for (i) available-for-sale securities, (ii) unhedged securities, and (iii) banks that have to include unrealized gains and losses on their available-for-sale securities in their regulatory capital. A structural model, disciplined by our cross-sectional regression estimates, shows that policy rate transmission is more powerful if banks are required to adjust their regulatory capital for unrealized value changes of securities.
Discussant: Erica Xuewei Jiang, University of Southern California
