David O. Lucca

Measuring Central Bank Communication: An Automated Approach with Application to FOMC Statements

The concept of semantic orientation (SO) seeks to evaluate a given word or phrase’s location on a semantic axis over which both direction and intensity of meaning can be defined. Operationally, a semantic axis is defined by two terms of opposite meaning, or antonyms—say, strong/weak, robust/fragile—which define direction and, by some given unit of measurement, intensity. In using their semantic expertise, human beings can subjectively categorize a sentence out of a statement. To a vast majority of readers the statement “Ernest Hemingway could kill a bear with his bare hands” will indicate strength rather than weakness, robustness rather than fragility. However, using the fuzzy logic of semantics leaves much potential for disagreements in terms of intensity and sometimes direction. The purpose of the automated SO procedures described in this Appendix is to provide an automated method of assigning such semantic values, which is objective, transparent, and easily replicable. The objectivity and replicability of the scores are relative to a reference corpus of text—in our implementation, the Internet and information from news outlets—on which the semantic orientation scores are based.

The Revolving Door and Worker Flows in Banking Regulation

This paper traces career transitions of federal and state U.S. banking regulators from a large sample of publicly available curricula vitae, and provides basic facts on worker flows between the regulatory and private sector resulting from the revolving door. We find strong countercyclical net worker flows into regulatory jobs, driven largely by higher gross outflows into the private sector during booms. These worker flows are also driven by state-specific banking conditions as measured by local banks’ profitability, asset quality and failure rates. The regulatory sector seems to experience a retention challenge over time, with shorter regulatory spells for workers, and especially those with higher education. Evidence from cross-state enforcement actions of regulators shows gross inflows into regulation and gross outflows from regulation are both higher during periods of intense enforcement, though gross outflows are significantly smaller in magnitude. These results appear inconsistent with a “quid-pro-quo” explanation of the revolving door, but consistent with a “regulatory schooling” hypothesis.

Credit Supply and the Rise in College Tuition: Evidence from the Expansion in Federal Student Aid Programs

We study the link between the student credit expansion of the past fifteen years and the contemporaneous rise in college tuition. To disentangle simultaneity issues, we analyze the effects of increases in federal student loan caps using detailed student-level financial data. We find a pass-through effect on tuition of changes in subsidized loan maximums of about 60 cents on the dollar, and smaller but positive effects for unsubsidized federal loans. The subsidized loan effect is most pronounced for more expensive degrees, those offered by private institutions, and for two-year or vocational programs.

Understanding mortgage spreads

Because most mortgages in the United States are securitized in agency mortgage-backed securities (MBS), yield spreads on MBS are a key determinant of homeowners’ funding costs. We study variation in MBS spreads in the time series and across securities and document that MBS spreads show a pronounced cross-sectional smile with respect to the securities’ coupon rates. We present a new pricing model that uses “stripped” MBS prices to identify the contribution of non-interest-rate prepayment risk to spreads and find that this risk explains the smile, whereas the time-series spread variation is mostly accounted for by nonprepayment risk factors.Received March 30, 2015; editorial decision November 21, 2018 by Editor Leonid Kogan. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Taking Orders and Taking Notes: Dealer Information Sharing in Treasury Markets

According to most theories of financial intermediation, intermediaries diversify risk, transform maturity or liquidity, and screen or monitor borrowers. In U.S. Treasury auctions, none of these rationales apply. Intermediaries submit their customer bids without transforming liquidity or maturity, and they do not screen and monitor borrowers or diversify fiscal policy risk. Yet, most end investors place their Treasury auction bids through an intermediary rather than submit them directly. Motivated by this evidence, we explore a new information aggregation model of intermediation. Intermediaries observe each client’s order flow, aggregate that information across clients, and use it to advise their clients as a group. In contrast to underwriting theories in which intermediaries, by acting as gatekeepers, extract rents but reduce revenue variance, information aggregators increase expected auction revenue, but also make the revenue more sensitive to changes in asset value. We use the model to examine current policy questions, such as the optimal number of intermediaries, the effect of non-intermediated bids, and minimum bidding requirements. ∗The views expressed here are the authors’ and are not representative of the views of the Federal Reserve Bank of New York or of the Federal Reserve System. We thank Ken Garbade, Luis Gonzalez, Richard Tang, Haoxiang Zhu and participants at the 2014 U.S. Treasury Roundtable on Treasury Markets for comments. Nic Kozeniauskas and Karen Shen provided excellent research assistance. Emails: nina.boyarchenko@ny.frb.org; david.lucca@ny.frb.org; lveldkam@stern.nyu.edu. Investors often access financial markets through intermediaries. Sometimes these intermediaries have exclusive access to a trading venue. Other times, they lower risk by screening investments or monitoring borrowers’ behavior. In U.S. Treasury auctions, which are the world’s largest, intermediaries channel investors’ bids, without diversifying or transforming risks. Further, in contrast to public offerings of private issuers (e.g., Beatty and Ritter, 1986; Hansen and Torregrosa, 1992), intermediaries in Treasury auctions cannot screen or monitor the issuer because they do not influence fiscal policy. Despite these limitations, and even though investors can bid directly through an electronic system, most bids are still placed through intermediaries. The prevalence of intermediation in a market where none of the typical rationales apply prompts us to examine a new role for intermediaries and its consequences for asset prices and auction revenue. We present a new theory of financial intermediaries who collect information from order flow, use it to advise clients, and bid for their in-house account.1 Existing work in the initial public offering (IPO) literature studies the effects of concentrated underwriting, which typically involves a single lead, or a handful of co-lead, underwriters. It finds that this structure lowers issuers’ revenues but also revenue variance.2 In Treasury auctions, there are many information intermediaries, investors have the option of bidding directly without an intermediary, and intermediaries are subject to minimum bidding requirements. Finally, intermediaries place very large bids for their own accounts. We show that in this setting, the conventional wisdom of underwriting is reversed: information intermediaries raise expected revenue but also revenue variance. By sharing valuable information with their clients, dealers lower clients’ risk, which encourages them to bid more aggressively and boost expected auction revenue. At the same time, more precise information about the asset value makes beliefs and bids more sensitive to changes in that value. Therefore, auction revenue is also more sensitive to information about the future value and as a result, more variable. Thus, information aggregation intermediaries provide value both for investors and for the asset issuer, but their effects on auction revenue are exactly the opposite from those of a traditional security underwriter. Sovereign auction rules regarding the use of client information vary across countries. In the UK, the Debt Management Office explicitly sanctions that Gilt-edged Market Makers, which have exclusive access to the auction and route orders for all other bidders, “whilst not permitted to charge a fee for this service, may use the information content of that bid to its own benefit” (GEMM Guidebook, 2011). We are not aware of similar rules in the context of U.S. Treasury auctions. In the U.S., a financial intermediary’s use of client information, including sharing such information with other clients or using the information for other benefit to such intermediary, may violate legal requirements, be they statutory, regulatory or contractual, and/or violate market best practices or standards. This paper does not take a view as to whether the described use of client information with respect to Treasury auction activity is legal or proper. The objective of the paper is to study the economic effects of order flow dissemination ahead of the auction as a mechanism to lower auction risk and raise revenues. In a “full commitment IPO,” the underwriter generally earns a large first-day secondary market return, and stabilizes the market value by raising supply elasticity, either offering additional (“greenshoe option”) or buying some of the securities being offered (Ritter and Welch, 2002).