ChatGPT-on-infrastructure-muni-bonds_federal-cost_-monopoly_rent-seeking-05132025-InRecap

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Yes, I know — ChatGPT cheerfully goes anywhere your questions lead (e.g., “Excellent framing — you’re getting to the core distortions caused by rent-seeking in the municipal bond market”). But maybe I’m just asking hard questions?

I’m not the only one. Here’s a quote from an article today in Governing magazine, Volatile Times in Muni Bond Land:

For the main reason that muni bonds will likely remain tax-exempt, look to the
mega-rich investors who contribute to political campaigns. Those are the people
who benefit most from tax-exempt bonds, and they are the ones in charge now. So
don’t kid yourself that it matters one whit to this regime whether New York or
Texas issuers might pay interest of 5 percent tax-free versus 5.7 percent taxable for
long-term muni bonds to build schools, housing and infrastructure. That’s not the
point anymore. Today, it’s ultimately about providing lucrative tax shelters for the
uber-rich. Politically, the local public purpose is now secondary.

For ChatGPT’s own trashing of the muni market this morning, you can judge for yourself — questions below. FWIW, I think the answers are mostly substantive. Maybe a muni bond proponent could upload the PDF and ask ChatGPT to rebut every point? Might try that myself, actually.

Bigger picture point: AI will have an impact on policy depth. The time and cost to quietly and discretely ask hard questions has been significantly reduced. But will the answers have an impact on policy direction? Who knows.

1. The muni bond tax exemption costs the federal government about $25 billion a year. How much of this cost can be attributed to muni bonds that are financing infrastructure projects? (page 1)
2. Yes, for water infrastructure [breakdown] — drinking water, wastewater, water management (e.g., flood control) (page 2)
3. If that $3.9 billion was provided to the WIFIA loan program as funding for credit subsidy, how much infrastructure could be built using WIFIA loans instead of tax-exempt bonds? (page 3)
4. In light of this result, and the fact of federal deficits, why is an expansion of WIFIA not being considered by Congress? (page 4)
5. Would not opposition from the municipal bond market lobby be a reason? This reason would operate ‘behind the scenes’ and not attract publicity. But the incentives are there. (page 6)
6. Is the muni bond market effectively a monopoly (or near-monopoly) provider of federally subsidized infrastructure finance in the US? (page 8)
7. If this near monopoly is being maintained by the power of the municipal bond market lobby, isn’t it an example of rent-seeking? (page 9)
8. How does such rent-seeking damage both federal taxpayers and the state & local governments financing infrastructure projects? For example, for the former, the windfall profits that go to high-income taxpayers instead of issuers. For the latter, the terms of muni bond financing reflecting retail investor preferences as opposed to optimizing the needs of state & local issuers. (page 11)
9. Yes [summarize a policy framework] (page 13)
10. Yes [draft ‘Policy Brief: Reforming Federal Infrastructure Finance to Maximize Public Value’] (page 16)

‘Narrative’ politics, as it has evolved over the last two decades, is a uniquely insidious force.

It appears able to displace consideration of reality even amongst a political leadership who are entrusted to know better. Yes, of course, there’s always been propaganda, spin, press plants, etc. But the ‘narrative force’ is different. Its power seems to originate from something completely new — advanced digital media. The printing press, mass-circulation newspapers, radio, television, even the early-stage internet — all mere precursors. Digital media puts it all together in terms of political impact.

Unchecked, the ‘narrative’ goes to absurd extremes. So absurd that a superior force — actual reality — eventually intervenes. I think this is what happened in 2024, which was, when you think about it, a veritable bonfire of unsustainable political and cultural narratives.

But so what? Fundamental economic and social questions are still not being addressed. Much of the pre-2024 narrative was not necessarily substantive. It may be better explained, especially in its distracting absurdity, as post-WFC camouflage for the continuation of business-as-usual. That business being various kinds of rent-seeking, extractive financialization, relentless wealth concentration, etc. In effect, the period 2008-2024 can be seen as an era of ‘narrative neoliberalism’.

Yes, Trump and his crew incinerated the camouflage, and it was fun to watch the well-deserved wrecking. But was the purpose to expose our hard reality and thereby start dealing with it? Or simply as an exercise in gaining political power, because a ‘counter-narrative’ can be as powerful a force as a reigning narrative?

Perhaps those are questions for future historians. But ‘what happens next?’ is far from academic. This is because, unlike any point in the US since 1945, fundamental issues need to be addressed. Kicking the can further down the road will have serious and inexorable consequences.

On the surface, the landscape looks chaotic. How could it be otherwise? The revolutionary regime is new and still consolidating its power, defenestrating long-entrenched opponents, performatively demolishing various iconic symbols of the ancien regime, and announcing (and often retreating from) radical decrees. Those on the losing side howl in outrage, to increasingly lesser effect, while they search for a way back in. The whole political circus is energized by a polarizing figure of unique genius for this purpose, Trump.

But underneath I am sure there are (there always are) serious people developing plans. They know the US faces fundamental issues that will drive fundamental change. Managing that change, and to what end, will be the critical challenges, and the fact of upheaval in itself frames the risks and opportunities. Note that agency within the frame is not limited to the revolutionaries who launched the upheaval, even after they’ve apparently consolidated their power. Far from it. You know the story — Robespierre to Napoleon, Kerensky to Lenin, to name just two. It’s entirely possible that follow-on revolutionaries or counterrevolutionaries, if they emerge, will make the current crew look tame.

Who knows what form these plans are taking? But I’m guessing that they’ll be roughly divisible into two opposing groups, if only because that seems to be a historical pattern. On the one side, there will be those with aspirations for deep reformation of government (and society, too, to the extent it can be influenced by government), as the way not only to comprehensively address near-term critical issues but to restore the nation to a better path. Of course, their idealistic visions will be tempered in due course, but a deep reformation will involve as a first step the dismantling of the existing order. Things will evolve from there. In my own narrow focus on loan programs, I already see some hints of a stern, reforming mindset, bent on dismantlement. Call this ‘post-neoliberalism’.

On the other side will be those for whom the current neoliberal arrangements have worked rather well. On a personal level, they can easily navigate any travails that unaddressed national issues might cause, and maybe even profit from the exercise. But it’d be a shame for such a lucrative enterprise to blow up completely, and so their plan will be focused on the various band-aids, emergency moves, quick patches and short-term repairs that will plausibly work, more or less, to keep the status quo going. The overall inadequacy of such ‘solutions’ for the nation will become apparent, but slowly at first. Much narrative force will be needed, once again, to camouflage the reality. But more robustly this time, and with less absurdity, because the impending reality will be, as it were, no joke. I assume they’ll steal and modify various parts of the post-neoliberal plan, especially the uplifting and aspirational bits — that’ll help keep people confused. Already, the ‘Abundance‘ narrative has that smell. Call this plan ‘neo-narrative neoliberalism’.

All interesting to observe, no? But at this point, I take sides, unequivocally. I have no doubt that post-neoliberal (or post-liberal, if they go that far) policies will be a hard and uncertain road to possible renewal of some kind. I don’t expect much, except a lot of work, and nobody else should either. Maybe there’ll be some virtue in this path, sometimes. It’s honest and real, or ‘reality adjacent’ anyway, and that seems important.

But neo-narrative neoliberalism is just a degenerate path to national suicide. It’s dishonest and corrupt, and even the prospect of seeing the ‘neo-narrative’ emerge in scale sickens me — what blatant and disgusting lies will they spin this time? What insults to our intelligence, what grotesque perversions of reality? An ever louder and more distracting carnival show of AI-fueled illusions to hide the depth of accelerating decay until rational thought becomes impossible? This is what they want?

I try to stay as neutral and realistic as possible in all political matters because it keeps things more analytically interesting. This one, this neo-narrative neoliberalism, however — I just hate.

So, taking sides is easy. No matter how little a post-neoliberal plan achieves, at least it opposes the other one. That’s sufficient for now, I think.

This was written before the 2026 Budget Summary was out but now even more relevant.

5/11/2025 Addendum: A Process of Clarification

After publication, a hearing expert witness contacted me with a clarification.  The reference to “small” WIFIA applications in the testimony was intended to mean applications from “small communities with big capital projects”.  Since WIFIA generally lends to bigger projects, while SRFs generally deal with smaller projects, the point was that regardless of borrower size, WIFIA should be enabled to support big projects with a small community funding base by offering a loan feature (sub-UST rates) that will help address their fundamental problem.

I don’t think that the clarification changes the main point I was making in the article: that WIFIA isn’t administratively set up to deal efficiently with such applications.  A big project with a small funding base is intrinsically risky, and SRFs are better positioned and experienced to deal with local project and credit risk.  If sometimes SRFs lack the loan capacity to do big projects, then WIFIA’s relatively efficient role here is to help add that capacity so that SRFs can utilize their strengths to finance these situations (which are apparently relatively widespread).

Maybe that’s a sufficient answer as far as the article goes.  But the clarification discussion made me think further.  Administrative capacity is a somewhat subjective metric, as well as being amenable to alteration (e.g., just add the right personnel and adjust the procedures).  Shouldn’t there be a more policy-oriented reason that sub-UST rates to smaller borrowers (with small or big projects) are outside WIFIA’s policy purpose?  After all, the larger point of the article is that the ‘new policy world’ makes it necessary to dig deeper and explain why the federal government should or should not be doing something, not only about how it might be done more efficiently or can’t be funded just now, as applicable.

Well, and to be fair to the expert witness, currently it is not clear why WIFIA should or should not be doing anything in particular (other than being generally helpful to the water infrastructure sector) because it and the other infrastructure loan programs have no explicit, precisely defined policy purpose.  So sure – sub-UST rates for small borrowers with big projects, why not?  Just add some admin capacity and the Program will be ready to go.  Who’s to say that’s mission creep when the mission is only defined by what Congress will fund? Why not ask, which is literally what the expert witness was doing in the hearing? Fair questions.

The need to address policy questions was implicitly surfacing at the hearing, but it became more evident, I think, in the 2026 WH Budget Summary.  In addition to proposing slashing cuts, that Summary makes some strong policy statements about the federal role in water infrastructure, like that “the States should be responsible for funding their own water infrastructure projects.”  Well, that certainly defines a mission, or more accurately, a non-mission, for federal policy. Doesn’t such a statement require an answer in kind?

I wrote a post about this after the WFM article was written but before that article was published: 2026 Budget Request: Policy Hints Amidst the Chaos. The Budget Summary’s radical cuts and associated policy rationales made me think that federal infrastructure loan programs might end up on somebody’s list. From that post:

“But here we are – if relevant policy directions and/or confusion [about federal support for water infrastructure finance] are emerging from the apparent chaos, they need to be addressed in the context of clear policy objectives. So, what are they? What should they be?

Here is where TIFIA, WIFIA and CWIFP have a serious problem. After you strip away all the special interest narratives, what exactly is the national purpose of federal infrastructure loan programs lending to investment-grade borrowers financing low-risk projects while debt markets are functioning normally? It could be reasonably said that there is none. In pre-2025 times, such an observation wouldn’t have mattered. Now, it might invite the DOGE chainsaw. So, a real-world, narrative-free objective, suited to the emerging political context and actual federal fiscal constraints, must be made explicit. For now, I’ll simply state what I think it should be:

The primary goal of federal infrastructure loan programs is to facilitate local funding for local infrastructure solely by utilizing intrinsic and unique federal financing strengths (relative to debt market alternatives) through loan feature design and efficient transaction implementation.“

With an explicit policy statement, the use of sub-UST rates at WIFIA can be clarified in a policy context:

• As noted in the article, a sub-UST loan has a grant (that is, funding) component.  Sub-UST loans for small borrowers with big projects would therefore be directly funding local projects.  Maybe the federal government should be doing that elsewhere, but it’s not WIFIA’s mission.

• Sub-UST loans to SRFs of course also have a grant component.  But the grant is not made to a local infrastructure project, but intended to improve a nationwide system of local lenders (by encouraging leverage) who will in turn have added capacity to facilitate local funding.  WIFIA, or more precisely SWIFIA, is — arguably — adhering to its mission in this case.

• While we’re at it, the federal government does not have any “intrinsic and unique” strengths in lending to small borrowers regardless of project size.  A national government can be made to do it, but it’s not good at it, relative to local lenders.  So WIFIA should stick to large, low-risk borrowers – a category which does include SRFs.

To be clear, you can agree or disagree with that policy statement, or you can propose something else. The point in the article and in the post, and one I’ll be making again, is that that’s the debate required for these times of federal upheaval.

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Of course, there’s a lot of speculation about deploying AI to replace federal employees for routine administrative tasks, and to make the remaining ones more efficient on those same tasks. Pretty obvious, I would think.

But what about the potential impact of AI on federal policy making? Not at all routine, often very complex, a lot of written output, almost always done under deadlines. Sounds a lot like university term papers, something which AI LLM models are apparently pretty good at. Will AI have an impact on federal policymaking?

It’s hard not to believe that AI LLM models are already in extensive (though perhaps unofficial) use by government policy staffers, not to mention think tanks, etc. For sure at DOGE — a house specialty, as it were.

So, as part of my ongoing exploration of AI using stuff I know about, I had a long-ish ‘discussion’ with the free version of ChatGPT about the WIFIA Loan Program. The unedited output is above.

Here’s my overall impression: Simple questions get ‘mainstream narrative’ answers because presumably that forms the bulk of the model’s database inputs. But if you push with harder, devil’s advocate-type questions, there’s much more subtlety and substance than I would have expected — there appears to be some synthesis of disparate sources and active ‘logic’ (or at least the appearance thereof) going on, and all expressed in eerily smooth and cogent language.

(Btw, as the model ‘contemplates’ and slowly scrolls out an answer, you get a visceral sense of physical effort: millions of chips firing away, heat rising from the frames, electricity pouring in and heated cooling water pouring out. All for one question on a free model. Now…how about that essential physical infrastructure again?)

It takes some knowledge to push the model into a deeper and logically sequential ‘exposition’ — you need to know what questions to ask. But in a policy-saturated environment, the staffer using the AI will probably have more than enough, just from their everyday general conversation. The purpose, cost and benefits of federal programs must be discussed all the time, one assumes (hopes?), even if little of those discussion ever becomes public. The federal programs are their ‘product’, and the day job is to put much thought into defending them — and attacking competing ‘products’. In that context, sophisticated users pushing AI to deliver deeper and more nuanced answers on policy issues, for defense, offense, or ‘war games’ will (or more likely, has) become commonplace.

The net result might be this: AI effectively lowers the cost and increases the efficiency of deep dives into policy matters. If there are equally sophisticated users on both sides of the issue (likely?), the whole policy discussion will likely have more than depth and nuance than before. Whether it’s ‘improved’ with respect to the public good might be another question (in one sense, AI ‘improves’ armed conflict — cui bono there?) and of course, everything will continue to be processed and packaged for public consumption, as always. Maybe it’s only safe to say for now that policy debate could become more interesting for dedicated and knowledgeable fans — a game played at a higher intellectual level, in effect.

The impact in this way on federal financing programs might be particularly significant. That’s because the combination of government policy and finance is intrinsically complex and multi-faceted — there’s a lot going on — and AI tools could be especially effective in efficiently digging out the nuances and synergies that otherwise wouldn’t be considered, e.g., by a hard-pressed staffer toiling away at 2 a.m. for a hearing the next day.

Well, we’ll see. In the meantime, below are the questions (with page numbers) I asked ChatGPT in the course of our ‘discussion’, starting from basic purpose and going to economic rationale, some political context, relationship to state & local lending funds and actual cost. Regarding the last one, you can see that I drilled the model pretty hard on a very specialized area, FCRA interest rate re-estimates. Its analysis and answers on that were surprisingly cogent. I’m not sure what to think about that yet.

Program Additionality

1. The WIFIA Loan Program lends to investment-grade public water agencies financing low-risk projects. But these agencies have many financial options, including access to the tax-exempt municipal bond market where interest rates are often as low as those offered by WIFIA. What purpose does WIFIA serve? Is the Program necessary? (page 1)

2. Does WIFIA compete with the municipal bond market? (page 3)

3. Is WIFIA necessary in terms of strict additionality? That is, given typical borrowers’ other finance alternatives, does it make any difference in terms of water infrastructure? (page 5)

4. Imagine you are trying to downsize and decentralize the federal government. Would WIFIA be a good candidate for elimination? Can state and other local governments perform the same function? (page 7)

Program Loans Based on Federal Financing Strengths

5. Does the federal government have any unique capabilities, relative to the debt markets or local governments, in providing infrastructure finance? Exclude transfer payment or loss absorption capability based on US scale. (page 9)

6. Are interjurisdictional coordination, mission-driven and regulatory leverage really financing strengths? Or just policy add-ons or riders that the federal government is enforcing by offering attractive financing terms? That is, offering a ‘carrot’ (the benefit) to get borrowers to accept the ‘stick’ (policy riders that they would not have otherwise done)? (page 12)

Program in Political Context

7. Is [WIFIA] ‘politically attractive’ to the [Biden] Administration? (page 14)

8. Try again. To the Trump Administration? (page 15)

9. How might DOGE people look at WIFIA Program? Are they likely to have a negative view? (page 17)

10. Could WIFIA have an essential role in water infrastructure finance based on federal functional financing strengths? For example, loan features like a very long term that can facilitate local funding for local projects. (page 18)

Program as a ‘Wholesale’ Lender

11. Would it also make sense for WIFIA to utilize unique functional strengths in lending to SRFs and other state & local infrastructure financing agencies? The rough analogy would be a ‘wholesale lender’ (WIFIA) to other local ‘retail lenders’ (state & local agencies). Could this a unique role? (page 20)

12. Would WIFIA make a good ‘retail lender’ (e.g. direct loans to many small projects throughout the country)? Why not? (page 23)

Program’s Actual Taxpayer Cost

13. A WIFIA loan has a ‘rate lock’ — the interest rate is locked at loan commitment, but loan drawdown may occur much later. Since cancelling the commitment if rates fall does not incur a penalty, doesn’t the rate lock work as an interest rate option? (page 24)

14. Per FCRA, the cost of a WIFIA loan to the taxpayers is estimated when the loan is drawn. If US Treasury rates have risen since loan commitment, the cost will exceed the discretionary appropriation allocated to the loan. The additional cost of such interest rates estimates will become an off-budget mandatory appropriation. Can you estimate the current scale of WIFIA’s off-budget mandatory appropriations? (page 26)

15. WIFIA borrowers can pre-pay their loans anytime without penalty. If interest rates fall, borrowers will refinance their loans. If rates rise, they will not. Over time, does this mean that the WIFIA loan portfolio will increasingly be concentrated in loans with low interest rates? (page 27)

16. Doesn’t this imply that the WIFIA Program is far more expensive than its discretionary appropriations would indicate? (page 29)

17. If DOGE conducts this kind of financial analysis on WIFIA, and estimates the true scale of Program cost, are they likely to recommend cutting it? (page 31)