And this may have been (technically and conceptually more advanced) Neanderthal art, also depicting a face.
OK, I realize that we don’t know for sure that this is a correct interpretation in either case. But interesting to contemplate.
And this may have been (technically and conceptually more advanced) Neanderthal art, also depicting a face.
OK, I realize that we don’t know for sure that this is a correct interpretation in either case. But interesting to contemplate.
It’s based on an ever-evolving talk that I gave multiple times in 2017, most recently at the interdisciplinary conference, “International Tax Policy in a Disruptive Environment,” that the Max Planck Institute for Tax Law and Public Finance held in Munich on December 14-15, 2017. A final version of the paper will be appearing in a forthcoming conference volume of the Bulletin for International Taxation, to be published by IBFD.
Its abstract goes something like this:
In the aftermath of the short but spectacular career of the destination-based cash flow tax (DBCFT) as a widely-discussed tax reform option in U.S. tax policy debate, this paper argues that we should generally move on from focusing on the DBCFT as a discrete package. While its political future (if any) is hard to predict, discussing it as a package tends to impede, rather than advance, clear thinking about the underlying issues.
Hayashi is interested in examining, from both a theoretical and an empirical perspective, the question of how the choice of tax base by local governments could affect the depth of recessions and speed of recovery within their borders.
In recent years, we have of course learned that serious recessions actually can and do still happen. Plus, they may be inadequately addressed at the federal level, despite the multiple tools of monetary policy, automatic fiscal policy adjustments, and discretionary fiscal policy responses. Plus, recessions may vary significantly in severity as between localities, even if geographical mobility within the United States is not quite so low as, say, that between distinctive parts of the EU.
So, even if one is skeptical of the potential of discretionary fiscal policy at the state and local level – if only due to balanced budget constraints on state and local governments – one might like to ask what automatic fiscal policy can do. Only, when one thinks about this, balanced budget constraints remain relevant.
State and local governments may face balanced budget legal requirements with varying degrees of rigor. But even if the legal constraints aren’t binding, the governments may face market constraints since, their credit ratings can plummet if they don’t take care (reflecting a long history of sub-federal defaults).
If a locality’s balanced budget constraint is sufficiently binding, then a countercyclical reduction in tax revenues may be promptly (or even verging on simultaneously) offset by a procyclical reduction in government outlays. So then the question becomes, from the standpoint of countercyclical fiscal policy, which of these two sets of opposite changes is likely to have a greater business cycle effect.
Joseph Stiglitz and Peter Orszag have apparently argued that marginal changes in state and local government spending, amid a recession, tend to affect consumption levels more than marginal changes in state and local tax levels – reflecting that taxes may tend to be paid by higher-income households that respond to the tax changes via their savings levels. If and insofar as this is true, one gets a seemingly paradoxical reversal of the standard wisdom regarding automatic fiscal policy.
If the tax side changed by itself, then the Keynesian macro standpoint would counsel the use by state and local governments of tax instruments that are relatively volatile and correlated with the business cycle. State and local income taxes are the classic example. By contrast, real property tax revenues tend to be extremely stable, even if home values are fluctuating. For example, property tax reassessments may be sporadic, may lean in practice against reducing the assessed value, and have enough discretion in the joints to permit keeping revenues steady. (Recent research by John Mikesell confirms that real property tax revenues were extremely stable during the Great Recession.)
So one has the paradigmatic choice between state and local taxes – income taxes, which fluctuate countercyclically but thereby draw procyclical spending changes, and real property taxes, which may fail to boost consumption in a recession, since they remain about the same, but have the virtue of not similarly drawing procyclical spending cuts.
A question of central interest in Hayashi’s paper is whether one can find an empirical correlation between (a) the use of income taxation versus property taxation at the county level and (b) the severity of and speed of recovery from recessions. Then a second question is whether one can draw a causal arrow from (a) to (b), based on the above scenario in which volatile income taxes, but not stable property taxes, draw matching spending cuts. Early work, reflected in the draft discussed yesterday, suggests that there may indeed be some positive correlation between using property taxes and doing better in recessions, but much work remains to be done before any causal interpretation of the data can be confidently advanced.
Given that point, what a bargain for them to have paid Paul Ryan’s fundraising committee a mere $500,000 shortly after the tax act passed. That’s only about 0.05% of a single year’s yield – although it’s obviously true that they’ve paid off plenty of other people as well.
Ryan of course also benefited, and got paid by, plenty of other very rich people by helping to ram through the tax bill. But still, without needing to compute who paid him how much in exchange for how much (and express, criminally punishable quid pro quos are wholly unnecessary to this), it is an interesting question, which the public choice literature has studied over a period of decades, why he and others like him can’t clear even more from their largesse than they already do.
Gordon Tullock wrote a number of interesting works, including this one, on why the Washington rent-seeking industry, although we think of it as large, is actually so small (and poorly paying for the government actors who provide the payoffs) relative to the benefits they provide. He noted that this suggests the industry is highly “inefficient” – a fact of which we should be glad, since if it were more “efficient” at rent extraction this would probably cause the collapse of the U.S. economy and immiserate (or further immiserate) the hundreds of millions of Americans who are not in a position to reap the fruits of perverting government processes.
One of the key factors Tullock identifies is that both legal constraints and informal norms, by making it harder to pay really large amounts and have explicit quid pro quo deals without courting jail time, help to make the industry so “inefficient.” But the rise of partisan norms, decline of democratic accountability, and decline of prosecutorial independence from the presidency (if sustained) could certainly move towards making the rent-seeking / corruption market increasingly “efficient.”
Forget draining the swamp; the question now is to what extent the swamp will start draining us.
Unfortunately for my comprehension, the article is in Japanese, but he suggested that I use Google Translate for the highlighted portion. I did so, and here is what I got:
“Mr. Trump often cites tax reductions of the Reagan administration about 30 years ago. However, Daniel Shaviro, who worked as a lawyer in planning a tax cut on Reagan, said, ‘At that time, the principle that equitable taxation should be imposed on whatever income it was in was at the bottom of the line: the current tax system to distinguish by how earned, It is not similar even though they are similar.'”
Hmm, not sure Google Translate absolutely nailed it here.
But perhaps I was noting that the passthrough rules cause the same earnings to be taxed differentially based on whether or not one is formally classified as an employee.
It’s a relief to be able to take a far less negative tone in my second piece addressing aspects of the 2017 act than in my first.
In the particular context of the 2017 act, suppose all that one changed was to base the centrally reported dynamic score numbers on gross national product (GNP), rather than gross domestic product (GDP). That would focus attention on the change in Americans’ wealth, rather than on growth in the U.S. economy without regard to how much of the value being produced was owned by foreigners. That would be no less “dynamic” a score. What is more, neither GNP or GDP is inherently a better measure. – it depends entirely on what one wants to know. But in context this would likely have been less misleading, as consumers of the dynamic score, and the growth effects it suggested, probably implicitly assumed that it was all to the benefit of U.S. individuals.
This brings me back to the point that dynamic scoring was pushed by people on the right as a weaponized tool to favor their side in the tax cut debate. This point is not contradicted by dynamic scoring’s having arguments in its favor, and indeed potentially improving information with regard to the particular narrow questions that it addresses.
This in turn calls less for rejecting it than recalibrating its use and seeking other tools to give greater prominence instead. These should both aim to supply useful information and to counter pervasive short-termism in the political budget process (possibly through different and complementary measures).
But a further question of interest is the following. Great, the right has had a shot at weaponizing the instruments used in budget debate in order to tilt the budgetary battlefield in its favor. Suppose people on the left wanted to do the same thing, only in their favor. Then what sorts of measures might they urge Congress, along with other information providers, to emphasize?
Here are three ideas that emerged from discussions that I had in relation to the colloquium. (I am putting it this way to minimize taking undue personal credit for ideas I got from other people, while also not directly reporting on the colloquium discussion, which was off the record.) None is anywhere close to fully formed or ready for primetime. They are rather possible directions for further thinking.
Idea #1 – dynamic scoring for growth-promoting public spending – For example, educational and infrastructure investment could have budget estimates that reduce the net cost by taking account of expected productivity gains and (perhaps separately) the tax revenue consequences of productivity gains.
Idea #2 – a measure that focuses on how tax changes affect inequality. This might be focused on high-end inequality (and separately on low-end inequality), and could take a number of different forms.
I don’t think that a Gini-style composite measure is at all useful here. It both conflates two quite distinct issues – high-end and low-end inequality – and is too bloodless and technocratic-looking.
Instead, some sort of measure that looks at gains to the top 1% and the top 0.1%. This could be put in a number of different ways, but the point is to have something that combines good optics with being intellectually defensible to focus attention on plutocrats’ gains from 2017-style tax changes.
Idea #3 – middle-class tax impact: Suppose one were to assume that unfunded tax cuts (or, say, income tax cuts) will be offset at some point by income tax increases, and that the latter will be proportionate to the different income percentiles’ shares of overall federal tax (or income tax) liability after adoption of the tax cuts. Hence, anything that cut taxes disproportionately for people at the top, a la the 2017 tax act, would be shown as increasing middle class taxes once the tax cut was funded in the specified manner.
In each of these cases, accurate information would actually have been provided. (In case 3, this pertains to the particular set of questions being asked, whether or not it’s true that the funding for the tax cut would definitely take that form.) So, no less than dynamic scoring, both may expand the information that policymakers have, only with a rather different focus on what questions are being asked.
Given that these ideas are still so preliminary and unformed, let me close here by making a more general point. This is not a matter of right or wrong – political players have every reason to try to tilt the process in their own favor – but I believe Republicans have, for decades, been much more active than Democrats in trying to shift the rules of various ongoing poltical games in their favor – whether we’re talking about districting, campaign finance, voting restrictions, budget rules, or budgetary information. This has led to asymmetric warfare that one could blame, if one is so inclined, more on the Democrats than on the Republicans.
Democrats ought as a matter of self-interest to address this. In the budgetary realm in particular, one thing they ought to do, if they take control of Congress in 2018 or later, is change the budgetary and information reporting rules, and much else as well, in their favor. It’s how the game is played these days. Dynamic scoring, other ways of doing dynamic scoring, and budgetary and information-providing rules more generally (in tax and elsewhere) are areas that they would be poring over carefully, if they were smart, in search of places to take advantage.
If the so-called wave emerges later this year, we will see if any of this actually happens.
But let’s start here with why one might want to do dynamic scoring. By saying that “one” might want to do it, I am abstracting for a moment from the political process, in which dynamic scoring is a weaponized tool pushed by those on the political right to advance their own subjective policy preferences, to ask only why it might be of interest to good faith players who wanted more and better information, even absent that entire side of things.
To set things straight from the start, conventional revenue estimates, no less than “dynamic” ones, are completely dynamic in a microeconomic sense. They build in, for example, the point that, if one doubled tax preferences for solar panels on people’s roofs, there would likely be a supply side response (more $$ spent by more people on such panels). What conventional revenue estimates treat as fixed is the macroeconomic side of things – aggregate labor supply, savings, available capital, etc.
Now, those things are not in fact fixed. They can change in response to a tax change, at least if it’s big enough and has some direct impact on them. So in principle one ought to take those things into account.
Suppose, for example, that the 2017 tax act actually would have paid in full for itself. That would have been worth knowing. And even if it, say, one-third pays for itself, that, too, is worth knowing.
Suppose further that members of Congress ask the staff: At what level do you project 2020 GDP, (a) without vs. (b) with a particular tax bill’s being enacted? It’s a reasonable question to ask, and one that merits a fully informed answer. But this brings us to the various “buts” regarding dynamic scoring, especially as practiced.
An iniital point is sharp dissensus among macroeconomic models. But that of course doesn’t mean we should have no such estimates, it just means they should be handled with care and that there should probably be multiple forecasts presented. (But JCT was instead told to provide a single operative estimate this time around.)
A second, more telling point, is that estimators are being asked to forecast incompletely specified policies. A budget forecast should be forward-looking for two reasons. One is that we should care about the future. The second is that actual economic actors may be forward-looking, so what they do may reflect their expectations about the future.
When there’s a preexisting fiscal gap, and a giant tax cut would make it even worse (even building in today’s actors’ expectations), the actual full set of policies, including the consequences of the set of pay-fors, remains unspecified. Now, this does not entirely defeat one’s making estimates about what will happen over the next ten years if the announced policies remain in force. But it creates a set of discontinuities – inside vs. outside the budget window, and announced vs. as yet unannounced policies – that can be misleading to policymakers and the public even if the 10-year forecast is accurate.
If there’s one fundamental political economy problem in budget policymaking, other than power imbalances and disregard for the interests of the less powerful, it’s short-termism. Politicians and voters want good stuff now without due regard for the nation’s future. (This is the subject, for example, of James Buchanan and Robert Wagner’s famous book, Democracy in Deficit.)
Dynamic scoring, when added to a budget window, accentuates short-termism. (One could reasonably argue, however, that the underlying problem is more about the budget window than dynamic scoring as such.) It gets back to the question that, as I noted in my prior post, policymakers might reasonably want to ask their staff: What would a given tax bill do, say, to GDP in 2 or 3 years? Revenue-losing tax bills such as the 2017 act have a tendency to increase short-term GDP growth in exchange for lowering it in the long run, due to fiscal crowdout. So while one ought to supply the information, one makes the political process worse if the result is to increase focus on the short term at the expense of the long term.
To put it another way, budget rules aren’t just about the quantum of information, they’re also about relative emphasis (as well as imposing specific constraints in particular cases, although the dynamic score was not used that way in 2017). Dynamic scoring as used – not necessarily, as an inherent conceptual thing – accentuates short-termism, when arguably the single most important thing that budget rules and scoring methodologies should do, apart from just supplying information, is to counter short-termism.
What happens if one puts dynamic scoring at the center of the process, and cares only about net revenue cost and GDP growth within the 10-year window? It’s possible that this would lead to one’s deriving the result that GDP would be the highest if federal revenue went all the way to zero – i.e., no taxes whatsoever.
To put it more precisely, the only way that wouldn’t be true is if crowd-out within the ten year period from having no tax revenues whatsoever, hence skyrocketing public debt and annual interest charges, sufficiently suppressed growth within the 10-year period by reason of crowd-out. Now this might happen in the forecast, even if estimators didn’t decide that they needed to consider modeling a full-blown fiscal crisis inside the budget window.
But there’s still a sense in which the wrong question (at least as a matter of emphasis) is being asked. If one centrally relies on dynamic scoring PLUS exclusive focus on the 10-year budget window, the optimal level of taxation appears to be that which would be optimal if (a) one had to pay interest charges and deal with crowd-out within the 10-year period, but also (b) at the end of 10 years, one got to cancel the public debt run-up – settle it for zero -without this having been anticipated or having adverse effects afterwards.
That is obviously not a sensible way to approach actual budget policy. As the Leiserson paper convincingly shows, dynamic scoring – again, conditioned on how it is being used, not necessarily in the abstract as one tool among dozens – creates bias in favor of ever larger tax cuts without offering any clue as to the fact that diminishing government revenues adversely affects people who therefore either get less from the federal government, now or in the future, or else end up paying more taxes later due to new enactments.
One last perspective that I want to offer with regard to dynamic scoring is its having been used as a “weaponized” tool in the federal budget and tax policy wars, and its not being the only possible weaponized tool, in support of the only existing interests, that one could imagine. But I will leave that point for a separate post that is to follow shortly.
At the session, Greg Leiserson of the Washington Center for Equitable Growth presented his very timely paper, “Removing the free lunch from dynamic scores: Reconciling the scoring perspective with the optimal tax perspective.”
Obviously, this paper comes in the immediate aftermath of the enactment of the 2017 tax act, in which “dynamic scoring” played what I would call a quasi-prominent role. I modify “prominent” with “quasi” because:
1) the regular score, not the dynamic score, was the one that ended up being used to measure compliance with the budget rule capping the revenue loss at $1.5 trillion,
2) due to the rushed process, the Joint Committee on Taxation wasn’t able to issue its dynamic score until late in the process, when the end result was verging on fixed and certain. So it doesn’t seem to have had any direct influence on what happened. Plus, once the score came out, showing an estimated dynamic revenue loss of about $1 trillion, Senate Republicans promptly rejected it for no good reason, based purely on their supposed intuitions.
Nonetheless, the score did matter atmospherically in a couple of ways that may linger. For one, it actually rebutted claims that the act would pay for itself, and even come close for doing so. For another, it did indeed predict a significant, albeit inadequate, growth response to the tax cuts, which it showed as reducing the revenue cost by about one-third.
As it happens, there are many reasons why I and others think that the $1 trillion dynamic revenue score was way too optimistic. Just as a starting point to motivate viewing it as very contingent, it’s based on weighted combinations of three radically different forecasting models, without disclosure as to what each of those models separately showed. JCT really hasn’t disclosed very much regarding the inputs to the dynamic aspect. But that says nothing as such about too low versus too high, except insofar as one might draw inferences from the extreme pressure JCT was under from its bosses to lean towards optimism, at least to the degree consistent with its incentive to limit harm to its own institutional reputation.
My reasons for thinking the score was probably too low, not too high, are as follows:
1) I think their regular score was too low, reflecting insufficient adjustment for the massive tax planning opportunities that the act has encouraged and that we will be reading about in the newspapers within a year or two, if not sooner.
2) There are several reasons for thinking the dynamic adjustments were too high. Perhaps the most important is that the model is based on assuming that other countries won’t respond by lowering corporate tax rates in response to what we’ve done. That’s an extremely unrealistic assumption, adopted solely because it’s outside their models to build in how other countries are likely to respond. But just because that’s hard to model (or outside their models) doesn’t mean it isn’t both likely and important.
3) My prior would have been to lean towards the Penn-Wharton budget model, which came out a bit higher.
All this is just background for Greg Leiserson’s paper. He is interested in dynamic scoring as an approach, not (for purposes of this paper) in whether the estimators got it right. He raises important challenges to what he calls the emerging consensus on how dynamic scoring is (and ostensibly should be) done. But I will save this set of issues for my next post.