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Record W2905380738 · doi:10.4324/9781315093284-35

Applying the Bierman Technique: Municipal Bond Bid Valuation

2017· book-chapter· en· W2905380738 on OpenAlexaboutno aff
Robert W. Zinn

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Reporting and Valuation Research
Canadian institutionsnot available
Fundersnot available
KeywordsValuation (finance)Municipal bondBondBusinessActuarial scienceFinance

Abstract

fetched live from OpenAlex

In the fall 1985 issue of Municipal Finance Journal , Professor Harold Bierman, Jr., analyzed and rejected the three commonly used methods for the valuation of competitively bid bond issues, putting forth instead a fourth technique of his own, the innovative none of the above (NOTA), or Bierman technique. In October 1991, Pinellas County successfully applied the Bierman technique to an actual bond issue, despite Daniel Anderson and the resistance of various underwriters, financial advisors, and bond counsels. The Bierman article defined four evaluational techniques, net interest cost (NIC), Canadian interest cost (CIC), present value, and NOTA. Florida municipal issuers generally award competitively bid bonds according to the true interest cost (TIC) method. TIC is defined as a discounted cash flow analysis, which is used by selecting a discount rate and applying it to a known future series of payments to calculate their present value.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.132
GPT teacher head0.343
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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