Bloomberg LLP is the main source of data for analysis. I collect data on school district advance debt refunding. The data give details on an advance refunded bond and include information on date of original issuance, date on which the issuer advance refunded, call date embedded in the bond, price of the bond on the call date, par value of the bond, time to maturity, coupon rate, and identity of the school district issuer.
I focus my analysis on Texas school districts. Hicklin (2004)emphasized the advantages of analyzing school district management outcomes within the setting of a single U.S. state, noting that it allows empirical testing of data from a single source and
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reduces measurement inconsistency. Texas is a unique choice for analysis due to two main reasons. The State is the leading source of school district advance refunding transactions among U.S. states. It accounts for the largest share of transactions both in terms of frequency and total par value, as shown in Appendix F.13 Texas also has a large and diverse population of school districts which allows for considerable variability in the data.The State accounts for 10.1 percent of the nation’s K-12 enrollments, second to California which constitutes 12.5 percent.
The study uses a random sample of 100 bonds, or CUSIPs, advance refunded by Texas school districts between January 1, 2005 and December 31, 2014. Using a random sample to analyze patterns in municipal bond markets is not uncommon in the academic literature. Zhang and Li (2004) used a sample of 61 municipal bonds to analyze advance refunding patterns. Similarly, Orr and de la Nuez (2014) created a random sample of 220 municipal bonds to analyze competing advance refunding policies. Also, Vijayakumar (1995) used a sample of 102 general obligation bonds to study state and local government advance refunding decisions. In the present study, I use a random sample of 100 advance refunded school district bonds to glean insights about the magnitude of option value loss among school districts, and to provide an empirical basis for future larger-scale
explorations of patterns in school district advance refunding outcomes in municipal bond markets.
Preliminary exploration of the 100, randomly selected, advance refunded Texas school district bonds reveals that the bonds are from 32 school district debt issuers spread across different geographical regions in Texas. These school district issuers also fall
13 State-specific statutes, fiscal rules and conventions may affect the extent to which school districts within a particular U.S. state undertake advance refunding of bonds.
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within the lower, middle, and upper levels of property tax revenue base. They also represent small, medium, and large enrolment size categories of Texas school districts. These variations in the sample should support inferences about the population of school district advance refunding transactions.
Computing option value loss requires information on uncertainty in future prices of the advance refunded bond. This option valuation parameter is explained in Section 3.4.3. I follow the approach in Ang et al. (2013) and use volatility in secondary market trade prices of an advance refunded bond as a measure of uncertainty in its future prices.14 Consequently, I gather information on all trades in a bond for each of the advance refunded bonds in the sample. This makes it possible to calculate uncertainty that is specific to the advance refunded bond. In all, I gather 7,800 observations of secondary market trade prices for the advance refunded bonds in the sample. Data on trade prices is from the Municipal Securities Rulemaking Board’s Electronic Municipal Market Access platform.
Option value loss computation also requires information on risk free interest rates. The link between risk-free interest rates and the magnitude of option value loss is
explained in Section 3.4.2. I use data from the U.S. Treasury’s State and Local Government Series (SLGS) interest rate tables. The SLGS emerged as a risk-free investment vehicle among state and local governments, following the federal
government’s restriction on investment of proceeds (e.g., from advance refunding) in
14 Using volatility in secondary market trade prices as a gauge of uncertainty in the future value of a bond seems to be the standard approach in the financial option valuation literature. Both Beatty and Ritter (1986) and Miller and Reilly (1987) explain how secondary market trade prices contain information about the value of securities in the primary market. Also, Green (2004) notes that “when some market participants have private information about the value of an asset, their trades reveal information to the market.” (p. 1201).
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higher-yielding instruments to earn arbitrage profits. Consequently, states, counties, cities, and school districts lock-in savings from advance refunding by placing proceeds in an escrow fund which holds yield-restricted U.S. Treasury securities (such as the SLGS) that match scheduled principal and interest payments on the advance refunded bonds (U.S. Department of the Treasury, 2011). In collecting data on SLGS rates, I ensure that the rates correspond to the life remaining in the advance refunded bond’s call provision.