Working papers of faculty, affiliated researchers and students at the Department of
Economics, University of California at Santa Barbara.
Exchange-rate economics is filled with puzzles. The asset approach has failed. Purchasing Power Parity is useful at best in the long run. There is no clear link between exchange rates and fundamentals. With no empirically supported theory for exchange rates, open-economy macro models are built on sand. This paper shows for the first time how recognizing differences between retail, wholesale and auction markets helps solve the puzzles, provides a theory of exchange rates based on auction markets for assets and commodities, and suggests a link between fundamentals and exchange rates.
Teh Forward-Bias Puzzle, failure of uncovered interest parity and related puzzles suggest that there is a fundamental failure in internatonal financial markets. Many theories attempt to explain this bias and failure. But none of them has been widely accepted; at least partly because they are not consistent with the related puzzles. The model of monetary policy in Table 6 explains the Forward-Bias Puzzle and the UIP failure without appealing to risk premia or information failures. It also explains, or is at least consistent with, the related puzzles. Finally it suggests that we need to change the way we think about UIP.
Uncovered interest parity is widely used in open economy macroeconomics. But the evidence rejects UIP and implies forward bias. There are many suggested explanations for the failure of UIP and forward bias, but none are widely accepted, at least partially because none appear to explain the related puzzles discussed below. This paper shows how sterilized “leaning against the wind” and a combination of inflationary and liquidity effects of open market operations can explain forward bias and the failure of UIP even when expectations are rational. They also appear to be able to explain the related puzzles.
Download rates of academic journals have joined citation rates as commonly used measures of research influence. But in what ways and to what extent do the two measures differ? This paper examines six years of download data for more than five thousand journals subscribed to by the University of California system. While down- load rates of journals are highly correlated with citation rates, the average ratio of downloads to citations varies substantially among academic disciplines. We find that, typically, the ratio of a journal’s downloads to citations depends positively on its im- pact factor. Surprisingly, we find that, controlling for citation rates, number of articles, academic discipline and year of download, there remains a “publisher effect,” with some publishers recording significantly more downloads than would be predicted from char- acteristics of their journals. Download statistics are recorded and supplied to libraries by journal publishers, often subject to confidentiality clauses. If libraries use download statistics to evaluate journals, they may want to account for publisher bias in these statistics.
Uncovered interest parity is widely used in open economy macroeconomics. But the evidence rejects UIP and implies forward bias. There are many suggested explanations for the failure of UIP and forward bias, but none are widely accepted, at least partially because none explain the related puzzles discussed below. This paper shows how the liquidity effects of open market operations and sterilized “leaning against the wind” can explain the failure of UIP and forward bias even when expectations are rational. They also appear to be able to explain the related puzzles better than any of the alternatives.
This paper explores the conditions under which there is "Coasian independence" between the assignment of property right and efficient allocation of resources.
We consider how the introduction of centralized netting in financial networks affects total netted exposures between counterparties. In some cases there is a trade-off: centralized netting increases the expectation of net exposures, but reduces the variance. We show that the set of networks for which expected net exposures decreases is a strict subset of those for which the variance decreases, so the trade-off can only be in one direction. For some network structures, introducing centralized netting is never beneficial to dealers unless sufficient weight is placed on reductions in variance. This may explain why, in the absence of regulation, traders in a derivatives network do not develop central clearing. Our results can be used to estimate margin requirements and counterparty risk in financial networks.