Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/150297
Authors: 
Geromichalos, Athanasios
Herrenbrueck, Lucas M.
Salyer, Kevin D.
Year of Publication: 
2016
Citation: 
[Journal:] Theoretical Economics [ISSN:] 1555-7561 [Volume:] 11 [Year:] 2016 [Issue:] 3 [Pages:] 897-935
Abstract: 
A consistent empirical feature of bond yields is that term premia are, on average, positive. The majority of theoretical explanations for this observation have viewed the term premia through the lens of the consumption based capital asset pricing model. In contrast, we harken to an older empirical literature which attributes the term premium to the idea that short maturity bonds are inherently more liquid. The goal of this paper is to provide a theoretical justification of this concept. To that end, we employ a monetary-search model extended to include assets of different maturities. Short term assets mature in time to take advantage of random consumption opportunities. Long term assets cannot be used directly to purchase consumption, but agents may liquidate them in a secondary asset market characterized by search and bargaining frictions. Our model delivers three results that are consistent with empirical facts. First, long term assets have higher rates of return in steady state to compensate agents for their relative lack of liquidity. Second, since the difference in the yield of short and long term assets reflects asset market frictions, our model predicts a steeper yield curve for assets that trade in less liquid secondary markets. Third, our model predicts that freshly issued (``on-the-run") assets will sell at higher prices than previously issued (``off-the-run") assets that mature in nearby dates, because sellers of the latter have a more urgent need for liquidity.
Subjects: 
Monetary-search models
liquidity
over-the-counter markets
yield curve
JEL: 
E31
E43
E52
G12
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by-nc/3.0/
Document Type: 
Article

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