Working Paper: NBER ID: w20746
Authors: Julien Hugonnier; Benjamin Lester; Pierre-Olivier Weill
Abstract: We study a search and bargaining model of an asset market, where investors' heterogeneous valuations for the asset are drawn from an arbitrary distribution. Our solution technique makes the model fully tractable and allows us to provide a full characterization of the unique equilibrium, in closed-form, both in and out of steady-state. Using this characterization, we first establish that the model generates aggregate trading patterns that are consistent with those observed in many over-the-counter asset markets. Then, we show that the model can replicate empirical regularities reported from micro-level data sets, including the relationships between the length of the intermediation chains through which assets are reallocated, the network centrality of the dealers involved in these chains, and the markup charged on the asset being passed along the chain. Finally, we show that heterogeneity magnifies the price impact of search frictions, and that this impact is more pronounced on price levels than on price dispersion. Hence, using observed price dispersion to quantify the effect of search frictions on price discounts or premia can be misleading.
Keywords: Decentralized Markets; Asset Pricing; Search Frictions; Heterogeneity
JEL Codes: D0; D53; D83; G12
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| model's framework (E17) | market dynamics (D49) |
| structure of the trading network (L14) | asset allocation (G11) |
| heterogeneity (D29) | price impact of search frictions (D83) |
| search frictions (F12) | price levels (E30) |
| search frictions (F12) | price dispersion (L11) |
| utility types distribution (L97) | trading frequency (G14) |
| utility types distribution (L97) | network centrality (D85) |
| trading frequency (G14) | trading volume (G15) |
| network centrality (D85) | markups along intermediation chains (D40) |