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On the Asset Pricing Implications of Incomplete Information in Sovereign Debt Markets

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posted on 2022-07-11, 20:56 authored by Santiago Tellez AlzateSantiago Tellez Alzate

In the first chapter, we investigate the asset pricing implications of disagreement about the unobservable process that drives monetary policy. We construct a monetary economy with two investors who have heterogeneous priors about the unobservable expected growth of money, namely, the underlying monetary stance. The key friction is that information about this unobservable variable is symmetric but incomplete. Investors estimate it from observed realizations of money supply in a Bayesian framework. Investors value real money holdings intrinsically, which gives rise to a demand for money. In equilibrium, the demand for money and investors’ estimates endogenously determine the nominal short rates and expected inflation through a portfolio rebalancing channel. Disagreement about money growth is one driver of the conditional variation in all nominal interest rates, expected inflation, and inflation risk-premium. Through a parameterized example, we show that the volatility of nominal interest rates tend to rise with increases in disagreement. We show that the relation between disagreement about money growth and asset prices crucially depends on the persistence of the unobservable growth rate of money. We further use the model to investigate the consequences of allowing for heterogeneous interpretations of public information (e.g. central bank statements) on interest rates. We introduce a public signal on which investors may have different views.

One steadfast investor believes the signal conveys relevant information about the unobservable process, while a doubtful one believes it contains only noise. Depending on the persistence of the unobservable process, interest rates may be more or less volatile in an economy populated by one steadfast investor and one doubtful investor that in an economy with two doubtful investors. In the second chapter, we propose a method to measure the importance of private information about fundamentals as a determinant of market power in the primary market for sovereign debt. The method is based on the estimation of a divisible good uniform price auction model presented in Vives (2010, 2011). We establish conditions under which the model is identified from bidding data. Through an application to the Colombian debt market, we show that private information decreases and inventory costs rise after the rebalancing of two emerging markets debt indices. These two findings have opposite effects on bid shading. The estimation results indicate that the change in revenue for the treasury is lower than two basis points of the par value of the bond offering. However, this result masks the economically meaningful impact that private informationand inventory costs separately have on market power. We use the model estimates to quantify the effect of these changes on bidders’ market po to reduce borrowing costs. Finally, in the third chapter, we provide model-free evidence that supports the estimated reduction in the importance of private information and the increase in inventory costs from our structural estimates. If bidders are privately informed in this market, then an auction’s cutoff price would reflect bidders’ private information about fundamentals that were not already captured by observable market prices. We show that auctions with high cutoff prices relative to a pre-auction benchmark predict high future secondary market prices. After the rebalancing, this effect either shrinks or vanishes altogether, consistent with a decline in the importance of private information. Furthermore, we find higher mean-reversion in inventories after the rebalancing. On average, it takes bidders 11.7 days to offload half of their inventories before the rebalancing, but only 7.5 days afterwards. Finally, we provide reduced-form evidence that is consistent with the assumptions regarding primary market participation from the theoretical model and our empirical identification and estimation strategies.

History

Date

2022-05-14

Degree Type

  • Dissertation

Department

  • Tepper School of Business

Degree Name

  • Doctor of Philosophy (PhD)

Advisor(s)

Burton Hollifield Pietro Bonaldi

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