Budget – Donald Marron

The 3-2-1 on Economic Growth: Hope for 3, Plan for 2, Pray it isn’t 1

How fast will the US economy grow? When mainstream forecasters consult their crystal balls, they typically see real economic growth around 2 percent annually over the next decade. The Congressional Budget Office (CBO) and midpoint estimates of Federal Reserve officials and private forecasters cluster in that neighborhood.

When President Trump looks in his glowing orb, he sees a happier answer: 3 percent.

That percentage point difference is a big deal. Office of Management and Budget director Mick Mulvaney recently estimated the extra growth could add $16 trillion in economic activity over the next decade and almost $3 trillion in federal revenues.

But could our economy really grow that fast? Maybe, but we’d need to be both lucky and good. We’ve grown that fast before. But it’s harder now because of slower population growth and an aging workforce. And there are signs that productivity growth has slowed in recent years.

To illustrate the challenge, I’ve divvied up past and projected economic growth (measured as the annual growth rate in real gross domestic product) into three components: the growth rates of population, average working hours, and productivity.

d_marron_20170807

The link between population and growth is simple: more people means more workers generating output and more consumers buying it. Increased working hours have a similar effect: more hours mean more output and larger incomes. Hours go up when more people enter the labor force, when more workers find jobs, and when folks with jobs work more.

Productivity measures how much a worker produces in an hour. Productivity depends on worker skills, the amount and quality of capital they use, managerial and organizational capability, technology, regulatory policy, and other factors.

As the first column illustrates, the US economy averaged 3 percent annual growth over more than six decades. Healthy growth in population and productivity offset a slight decline in average hours. Of course, that six-decade average includes many ups and downs. The Great Recession and its aftermath dragged growth down to only 1.4 percent over the past decade. In the half century before, the United States grew faster than 3 percent.

Mainstream forecasters like the CBO and the Federal Reserve expect slower future growth along all three dimensions. People are having fewer children, and more adults are moving beyond their child-rearing years, so population growth has slowed. Our workforce is aging. Baby boomers are cutting back hours and retiring, and younger workers aren’t fully replacing them, so average working hours will decline. Productivity growth has slowed sharply in recent years, for reasons that are not completely clear. Productivity is notoriously difficult to forecast, but recent weakness has inspired many forecasters to expect only moderate growth in the years to come.

Proponents of President Trump’s economic agenda offer a rosier view. Four prominent Republican economic advisers—John F. Cogan, Glenn Hubbard, John B. Taylor, and Kevin Warsh—recently argued that policy, not just demographic forces, has brought down recent growth. They claim supply-side policy reforms—cutting tax rates, trimming regulation, and reducing unproductive spending—can bring it back up. They argue that encouraging investment, reinvigorating productivity growth, and drawing enough people into the labor force to offset the demographic drag would generate persistent 3 percent growth.

Many analysts doubt such supply-side efforts can get us to 3 percent growth (e.g., here, here, here, and here). Encouraging investment and bringing more people into the labor force could certainly help, but finding a full percentage point of extra growth from supply-side reforms seems like a stretch. Especially if you plan to do it without boosting population growth.

The most direct supply-side policy would be expanding immigration, especially among working-age adults (reducing our exceptional rates of incarceration could also boost the noninstitutional population). But the Trump administration’s antipathy to immigration, and that of some Republicans in Congress, pushes the other way. Cutting legal immigration in half over the next decade could easily take 0.2 percentage points off future growth (see this nifty interactive tool from ProPublica and Moody’s Analytics). Three percent growth would then be even more of a stretch.

Another group of economists believes that demand-side policies—higher spending and supportive monetary policy—could lift growth above mainstream forecasts.

One trio of economists took a critical look at past efforts to forecast potential GDP growth, a key driver of long-run growth forecasts. They conclude that forecasters, including those at the Federal Reserve and the CBO, have overreacted to temporary economic shocks, overstating potential growth when times are good and understating it when times are bad. We’ve recently had bad times, so forecasters might be underestimating potential GDP almost 10 percent. If so, policies that boost demand could push up growth substantially in coming years. (For a related argument, see here.)

So where does that leave us?

Well, every crystal ball (and glowing orb) is cloudy. We should all be humble about our ability to forecast the economy over the next decade. Scarred by the Great Recession and its aftermath, forecasters may be inadvertently lowballing potential growth. Good luck and good supply- and demand-side policies might deliver more robust growth than they anticipate. But those scars remind us we can’t always count on good policy, and luck sometimes runs bad.

We can hope that luck and good policy lift growth to 3 percent. But it’s prudent to plan for 2 percent, and pray we don’t fall to 1 percent.

Outside Research Organizations Can’t Replace CBO’s Budget Team

The House Freedom Caucus wants to eliminate the Budget Analysis Division at the Congressional Budget Office and rely on outside research organizations, including the Urban Institute, instead. As a former acting director of CBO and an Institute fellow at Urban, I think this is a terrible idea. It would harm fiscal policymaking and weaken the Congress.

Here’s the proposal offered by Representatives Scott Perry (R-PA), Jim Jordan (R-OH), and Mark Meadows (R-NC):

The Budget Analysis Division of the Congressional Budget Office, comprising 89 employees with annual salaries aggregating $15,000,000, is hereby abolished. The duties imposed by law and regulation upon the employees of that Division are hereby transferred to the Office of the Director of the Congressional Budget Office, who shall carry out such duties solely by facilitating and assimilating scoring data compiled by the Heritage Foundation, the American Enterprise Institute, the Brookings Institution, and the Urban Institute.

We certainly appreciate the shout out. Here at Urban, we have amazing researchers who model policies involving health insurance, Social Security, taxes, food stamps, housing, and many other programs. We are proud of our work and try to be as helpful as possible to lawmakers across the political spectrum.

But neither we nor other private organizations can replace CBO’s budget group. Our skills overlap, but we fill different niches in the policy ecosystem.

Consider the sheer scope of CBO’s responsibilities. As Director Keith Hall noted in recent testimony, the agency expects to publish official scores of more than 600 pieces of legislation in the next year. The scores will estimate the spending and, usually with input from the Joint Committee on Taxation, the revenue implications of every provision in those bills. They will also assess whether the bills impose substantial mandates on the private sector or state, local, and tribal governments.

To do this, CBO has staffers familiar with every nook and cranny of the government, from agriculture to veterans. In just the past week, CBO has published more than two dozen cost estimates covering everything from flood insurance to child care to maritime administration to sanctions on Russia, Iran, and North Korea. Not to mention scoring Senate proposals to repeal and possibly replace the Affordable Care Act. Only CBO and its White House equivalent, the Office of Management and Budget, have the capacity to model every facet of federal spending.

Outside groups could certainly expand their capacities. And Congress could expand the list of anointed organizations. But the bottom line is that we would need substantial new resources, both funding and people. Replacing the capacities of CBO’s budget division is not something research organizations can or should do for free.

But resources aren’t the core issue. In addition to its published cost estimates, CBO provides thousands of confidential cost estimates to members of Congress and their staffs as they craft potential legislation. This service is vital to thoughtful legislating. Confidential feedback helps members test new ideas, consider alternatives, and refine proposals until they are ready to go public.

Outside organizations can, and indeed already do, provide similar modeling help to members. At Urban, we frequently get requests from Representatives and Senators of both parties. But working through iterations of potential legislation works best when lawmakers and their staffs work directly with the analysts who will give them official scores. Working with CBO’s budget team is a much more effective process than trying to coordinate different scores, based on different models and assumptions, from multiple outside organizations.

The most important difference between research organizations and Congress is also the most obvious. CBO works for Congress and only for Congress. CBO works closely with the budget committees and House and Senate leadership to juggle priorities, set deadlines, and provide the analyses Congress needs and wants. CBO obeys congressional budget rules, even when it disagrees with them. CBO has the backing of Congress when it gathers data and information from agencies.

CBO thus has an edge in providing the analyses Congress needs, when it needs them. Research organizations can and do provide timely analysis as well, but there are limits. We have other projects and demands on our time.

Moreover, we outside researchers rely heavily on the work that CBO’s budget analysis division currently does. CBO’s annual baselines, for example, often provide the starting point for our analyses. And CBO scores provide many of the numbers we use to model alternative policies. Eliminating CBO’s budget team would undermine our ability to deliver the type of analyses that Congress wants.

Eliminating CBO’s budget team would also weaken Congress. Congress created CBO in the early 1970s as part of a larger battle with President Nixon about power over the purse. Congress created CBO to ensure its own source of credible budget information. Defunding CBO’s budget team would weaken Congress at a moment when objective budget information and a balance between Congress and the President are as important as ever.

My colleagues and I would welcome opportunities to provide more help to Congress as members grapple with policy challenges, develop options, and try to understand the range of potential outcomes. But asking us to replace CBO’s budget team would undermine thoughtful policy making and weaken the Congress.

Budgeting for Federal Lending Programs Is Still a Mess

On Monday, the Government Accountability Office (GAO) defended the current method for budgeting for federal lending programs, known as “credit reform.” By endorsing the status quo, GAO puts itself at odds with the Congressional Budget Office (CBO), which has championed a “fair value” alternative. The details are wonky but the stakes are big. Over a decade, federal lending support for mortgages, student loans, and the Export-Import Bank could appear $300 billion more costly under fair-value budgeting than under credit reform.

CBO is right to question the way we budget for these programs. But GAO is right that CBO’s version of fair value is the wrong solution. Instead, we need a new approach that captures the strengths of both ideas, while avoiding their flaws. I laid out that alternative in a recent report.

One reason we need a new approach is that credit reform violates fundamental principles of good budgeting, for reasons that have nothing to do with the fair value debate.

The problem

Credit reform uses present values to measure the budget impact of federal loans, recording any expected gains or losses the moment a loan is made. But the rest of the budget operates on a cash basis, recording the budget effects of tax and spending policies as they happen over time. These two approaches do not mix well together. By using present values, credit reform can make federal lending appear to mint money out of thin air. It also credits the budget today for earnings it won’t see until well beyond the official budget window.

Consider a simple example: the government lends $1,000 to a business for four years expecting a 4 percent annual return, or $40-a-year for a total of $160. To finance the loan, the government issues $1,000 in Treasury bonds that pay 1.5 percent interest. At $15 per year, interest costs total $60. Thus, the government would net $100.

New New Table

How should we budget for those expected gains? One possibility would be to track cash flows, as we do for other government activities. The government lends $1,000 in year one, nets $25 in each of the four following years, and gets repaid $1,000 in year five. Its overall gain would be $100, just as it should be.

That gets the cash flows right, but the timing is ill-suited to budgeting. The upfront cost can make the loan look costly even though it actually brings in money. If Congress focused on a three-year budget window, for example, the loan would look like it costs $950 even though it actually earns $100 over its full life.

A poor solution

We can avoid that problem by eliminating the confusing lumpiness of the cash flows. Credit reform does so by calculating the net present value of the return on the loan, discounted using the government’s borrowing rate. That calculation (the second row in the table) shows an instant gain of $96 when the loan is made. (The $96 is slightly less than the $100 because of pesky technical details.)

Credit reform thus eliminates the lumpiness but at a big cost: it misleadingly claims the returns to lending happen instantly. In reality, those returns accumulate gradually over the life of the loan. In its zeal to get rid of the lumpiness bathwater, credit reform mistakenly throws out the timing baby. As a result, lending programs can look like a magic money machine.

Unlike tax increases or spending cuts, lending programs get instant credit for returns they won’t see for years, sometimes far beyond the official budget window. To take an extreme case, a 100-year loan on the above terms would score as almost $1,300 in immediate budget gains under credit reform, all before the government collects a dime in interest.

To the best of my knowledge, no other person, business, or organization budgets or accounts for loans this way (please share any counterexamples; Enron doesn’t count). Instead, they either accept the lumpiness of the cash flows or use an approach that avoids the lumpiness while reflecting the real timing of returns.

A better answer

It isn’t hard: Instead of tracking all the cash flows, we can report just the net returns on the loan. When the loan is first made, there aren’t any. In our example, the $1,000 loan exactly offsets $1,000 in borrowing to finance it. The reverse happens in year five when the loan gets paid off. In between, the government nets $25 each year: $40 in interest payments less $15 in annual financing costs.

Tracking net returns is a highly intuitive way to report the budget effects of making the loan. It would match the way we budget for tax and spending programs, and would respect the budget window.

The government can and sometimes does make money from its lending programs, but not instantly. The budget community should disavow the credit reform approach and recognize that earnings accumulate gradually over time. CBO, GAO, and budget wonks should join hands to fix this problem regardless of where they sit in the fair value debate.

Note: For more on the technical details, including how to deal with loan guarantees, how the fair value debate reappears in deciding how to measure net returns, and a second challenge in budgeting for lending programs, see my report and policy brief.

How Should We Use the Revenue from Taxing Carbon?

Adele Morris co-authored this post.

A US carbon tax could raise $1 trillion or more in new revenue over the next decade. There is no shortage of ways to use it.

Tax reformers want to cut business and personal taxes. Budget hawks want to reduce future deficits. Environmental advocates want to invest in clean energy. Progressives want to expand the social safety net. And so on.

How should we make sense of these competing ideas? In a new policy brief, we suggest a framework for thinking through these options. We identify four basic uses of carbon tax revenues:

Offset the new burdens that a carbon tax places on consumers, producers, communities, and the broader economy;
Support further efforts to reduce greenhouse gas emissions;
Ameliorate the harms of climate disruption; or
Fund public priorities unrelated to climate.

Each has merit, especially as part of an effort to build a political coalition to enact and maintain a carbon tax. But some ideas have more merit than others.

On both policy and political grounds, it makes sense to use carbon tax revenue to soften the blow on lower-income households and coal workers and their communities. Doing so will require only a small fraction (15 percent or so) of carbon tax revenue, leaving substantial resources for other purposes.

Recycling revenue into broader cuts in personal and business taxes also has particular merit. It can help offset the economic burden of the carbon tax and facilitate pro-growth tax reforms. By assuaging concerns that a carbon tax is just another way to expand government, moreover, revenue recycling may be essential to enacting a tax. However, requiring strict revenue neutrality also has downsides. Some policy goals, such as assistance to displaced coal workers, could be better pursued by spending the money directly, rather than indirectly through the tax system.

Policymakers should approach other uses of carbon tax revenue with more caution.
For instance, they should be careful in using revenues to try to cut emissions further. A well-designed carbon tax would do a good job reducing greenhouse gas emissions, so additional policy initiatives should focus on filling in gaps—reducing emissions the tax may miss. Merely duplicating efforts—e.g., supporting clean electricity facilities—would not be cost effective. Indeed, policymakers could roll back tax credits for solar and wind power and other subsidies and mandates that a sizable carbon tax would make redundant. That would free up resources to pursue other, more beneficial goals.

Policymakers should be similarly cautious about tightly linking revenue to specific new spending, whether climate-related (e.g., coastal protection) or not (e.g., new highways). Earmarking risks overspending on any one line item, deploying resources inefficiently, and fueling concerns that the tax would become a slush fund for politicians’ pet projects.

Decarbonizing the economy requires long-term solutions. Many emissions-reducing investments involve large expenditures on long-lived capital, such as power plants and industrial facilities. A carbon tax package that businesses and people believe will endure will be more environmentally successful than one that people think may not survive the next election.

In Australia, for instance, a carbon tax that took effect in 2012 was repealed just two years later, an object lesson in how highly partisan climate policies can be rescinded by future governments. Policymakers should thus give special attention to identifying revenue uses that build ongoing support for a carbon tax.

What Should We Do with the Money from Taxing “Bads”?

What do indoor tanning, shopping bags, junk food, alcoholic beverages, tobacco, “gas guzzling” cars, ozone-depleting chemicals, sugary drinks, marijuana, gasoline, coal, carbon-containing fuels, and financial transactions have in common? Taxes that discourage them. The United States taxes indoor tanning to reduce skin cancer, for example, while Washington DC taxes shopping bags to cut litter, and Mexico taxes junk food to fight obesity.

Governments hope these “corrective taxes” will reduce harms from pollution, unhealthy consumption, and other risky behaviors. But taxing “bads” can also bring in big money. A US carbon tax could easily raise more than $100 billion annually, for example, and a tax on sugary drinks could raise $10 billion.

How should governments use that money? As you might expect, policymakers, advocates, and analysts have proposed myriad ways to use the revenue to pay for new spending, to cut taxes, or, in a few cases, to reduce borrowing. In a new paper, however, Adele Morris and I argue that all these options boil down to four basic approaches:

Revenue Use Table 2

Advocates often suggest that revenue be put toward the same goal as the tax. Carbon tax revenues might subsidize energy efficiency or clean energy, for example, and sugary drink revenues might subsidize healthier food or nutrition information programs. Using revenue that way may make sense if you believe the tax won’t sufficiently change business and consumer choices. But there are downsides. A successful tax will typically reduce the potential benefits from other policies aimed at the same goal. As a result, it may make sense to roll back other policies, rather than expand them, when a substantial corrective tax is implemented. Directing revenues to the same goal may also limit lawmakers’ ability to build a coalition for a corrective tax, while other uses may attract supporters with other priorities.

Another approach is to use the revenue to offset the burdens that a corrective tax creates. New taxes on food, energy, and other products can squeeze household budgets, particularly for families with lower incomes. Shrinking the market for targeted products may disproportionately burden specific workers, industries, and communities. If a tax is large enough, moreover, it may slow overall economic activity. Tax cuts, expansions in transfer programs, or other spending increases may offset some of these harms while leaving the incentives intact. This is particularly important when taxes are intended to help people who suffer from internalities—health risks and other costs they unintentionally impose on themselves. In those cases, rebating revenue to affected consumers can help ensure that a tax actually helps the people who pay it.

A third approach is to use revenues to offset costs of the taxed activity. If an activity imposes costs on an identifiable group of people, it may make sense to compensate them for the harm. A US tax on coal does this, for example, by funding assistance to workers who develop black lung disease. Revenues can also cover some costs of providing public services that support the taxed activity. Fuel taxes paid by drivers, airplane passengers, and maritime shippers , for example, help fund the creation and maintenance of the associated infrastructure.

Finally, governments could treat corrective taxes like any revenue source, with receipts used to reduce borrowing, boost spending, or cut taxes in ways unrelated to the goal of the tax. Governments could allocate the money using ordinary budget processes, as Berkeley, California does with its soda tax revenue, or could earmark revenues to specific efforts, as France does by directing some financial transactions tax revenue to international aid.

Policymakers must consider a host of factors when deciding what mix of these options to pursue. Complete flexibility may allow them to put revenue to its best use over time. But surveys suggest that the public is often skeptical of corrective taxes if they don’t know how the revenue will be used. Many worry, for example, that the corrective intent of a tax may just be a cover story for policymakers’ real goal of expanding government.

Recycling corrective tax revenue into offsetting tax cuts can assuage that concern. But revenue neutrality has downsides as well. Matching incoming revenues and offsetting tax cuts may be difficult, given uncertainties in future revenues from a corrective tax and any offsetting tax cuts. In addition, it may be easier to achieve some distributional goals through spending than tax reductions. For example, a new spending program may be a more straightforward way to help coal miners hurt by a carbon tax than some kludgy tax credit. People who generally oppose wholesale revenue increases from corrective taxes should thus be open to modest deviations from revenue neutrality that provide a more effective way to accomplish policy goals.

Everything You Should Know about Taxing Carbon

Climate change is hot. From the pope’s encyclical to the upcoming United Nations conference in Paris, leaders are debating how to slow and eventually stop the warming of our planet.

We economists think we have an answer: put a price on carbon dioxide and the other gases driving climate change. When emissions are free, businesses, consumers, and governments pollute without thinking. But put a price on that pollution and watch how clean they become.

That’s the theory. And it’s a good one. But translating it from the economist’s whiteboard to reality is challenging. A carbon price that works well in principle may stumble in practice. A real carbon price will inevitably fall short of the theoretical ideal. Practical design challenges thus deserve close attention.

To help policymakers, analysts, and the public address those challenges, Eric Toder, Lydia Austin, and I have published a new report, “Taxing Carbon: What, Why, and How,” on putting a price on carbon.

Some highlights:

Lawmakers could put a price on carbon either by levying a tax or by setting a limit on emissions and allowing trading of emission rights. These approaches have much in common. Politically, however, a carbon tax is on the upswing. Cap and trade failed in 2010, while interest in taxing carbon is growing, including three bills in Congress and endorsements from analysts of diverse ideological stripes.

Carbon prices already exist. At least 15 governments tax carbon outright, and more than 25 have emissions trading systems. Those efforts have demonstrated that the economists’ logic holds. If you put a price on carbon, people emit less.

Figuring out the appropriate tax rate is hard. The Obama administration estimates that the “social cost of carbon” is currently about $42 per metric ton. But the right figure could easily be double that, or half. That uncertainty is not a reason to not tax carbon. But it does mean we should maintain flexibility to revisit the price as new evidence arrives.

Taxing carbon could reduce the need for regulations, tax breaks, and other subsidies that currently encourage cleaner energy. Rolling back those policies, in particular EPA regulations for existing power plants, may make policy sense and will likely be essential to the politics of enacting a carbon tax. But the details matter. Rolling back existing policies makes more sense with a carbon tax that’s high and broad, than with one that’s low and narrow.

By itself, a carbon tax would be regressive: low-income families would bear a greater burden, relative to their incomes, than would high-income families. We can reduce that burden, or even reverse it, by recycling some carbon revenue into refundable tax credits or other tax cuts focused on low-income families.

By itself, a carbon tax would weaken the overall economy, at least for several decades. That too can be reduced, and perhaps even reversed, by recycling some carbon revenue into offsetting tax cuts, such as to corporate income taxes.

Unfortunately, there’s a tradeoff. The most progressive recycling options do the least to help economic growth. And the recycling options that do the most for growth would leave the tax system less progressive.

A global agreement on carbon reductions would be preferable to the United States acting alone. Given the nation’s size and contribution to global emissions, a unilateral tax would make a difference, but would damage the competitiveness of some US industries. Special relief for these sectors could reduce the benefits of the tax, but may be necessary both practically and politically.

A carbon tax won’t be perfect. Done well, however, it could efficiently reduce the emissions that cause climate change and encourage innovation in cleaner technologies. The resulting revenue could finance tax reductions, spending priorities, or deficit reduction—policies that could offset the tax’s distributional and economic burdens, improve the environment, or otherwise lift Americans’ well-being.

The challenge is designing a carbon tax that delivers on that potential. We hope our new report helps elevate what will surely be a heated debate.

Three Things You Should Know About Dynamic Scoring

The House recently changed the rules of budget scoring: The Congressional Budget Office and the Joint Committee on Taxation will now account for macroeconomic effects when estimating the budget impacts of major legislation. Here are three things you should know as we await the first official dynamic score.

1. Spending and regulations matter, not just taxes

You might think dynamic scoring is just about taxes. It’s not. Spending and regulatory policies can also move the economy. Take the Affordable Care Act. CBO estimates that the law’s insurance subsidies will reduce labor supply by 1.5 to 2.0 percent from 2017 to 2024, some 2 to 2.5 million full-time equivalent workers. If CBO and JCT do a dynamic score of the House’s latest ACA repeal, this effect will be front and center.

The same goes for immigration reform. In 2013 (and in 2006), CBO and JCT included some macroeconomic effects in their score of comprehensive immigration reform, though they did not do a fully dynamic score. Under today’s rules, reform would show an even bigger boost to the economy and more long-term deficit reduction than the agencies projected in the earlier bills.

2. Dynamic scoring isn’t new

For more than a decade, CBO and JCT have published dynamic analyses using multiple models and a range of assumptions. For example, JCT projected former House Ways & Means Committee chairman Dave Camp’s tax reform plan would boost the size of the economy (not its growth rate) by 0.1 to 1.6 percent over 2014 to 2023. The big step in dynamic scoring will be winnowing such multiple estimates into the single set of projections required for official scores.

Observers understandably worry about how the scorekeepers will do that. For example, what will JCT and CBO do with certain forward-looking models that require assumptions not just about the policy in question but also about policy decisions Congress will make in the future? If the agencies score a tax cut today, do they also have to include future tax increases or spending cuts to pay for it, even if Congress doesn’t specify them? If so, how should the agencies decide what those offsetting policies are? Does the existence of such models undermine dynamic scoring from the start?

Happily, we already have a good sense of what the agencies will do, and no, the existence of such models doesn’t hamstring them. At least twice a year, CBO and JCT construct baseline budget projections under existing law. That law often includes scheduled policy changes, most notably the (in)famous “fiscal cliff” at the end of 2012. CBO and JCT had to include the macro effects of the cliff in their budget baseline at that time, even though they had no idea whether and how Congress might offset those policies further in the future. That’s dynamic scoring in all its glory, just applied to the baseline rather than analyzing new legislation. CBO and JCT didn’t need to assume hypothetical future policies to score the fiscal cliff, and they won’t need to in scoring legislation either.

3. Dynamic scoring won’t live up to the hype, on either side

Some advocates hope that dynamic scoring will usher in a new era of tax cuts and entitlement reforms. Some opponents fear that they are right.

Reality will be more muted. Dynamic scores of tax cuts, for example, will include the pro-growth incentive effects that advocates emphasize, leading to more work and private investment. But they will also account for offsetting effects, such as higher deficits crowding out investment or people working less because their incomes rise. As previous CBO analyses have shown, the net of those effects often reveals less growth than advocates hope. Indeed, don’t be surprised if dynamic scoring sometimes shows tax cuts are more expensive than conventionally estimated; that can easily happen if pro-growth incentives aren’t large enough to offset anti-growth effects.

Detractors also worry that dynamic scoring is an invitation for JCT or CBO to cherry pick model assumptions to favor the majority’s policy goals. Doing so runs against the DNA of both organizations. Even if it didn’t, the discipline of twice-yearly budget baselines discourages cherry picking. Neither agency wants to publish rosy dynamic scenarios that are inconsistent with how they construct their budget baselines. You don’t want to forecast higher GDP when scoring a tax bill enacted in October, and have that GDP disappear in the January baseline.

I am cautiously optimistic about dynamic scoring. Done well, it can help Congress and the public better understand the fiscal effects of major policies. There are still some process issues to resolve, most notably how investments might be handled, but we should welcome the potential for better information.

For more views, see the dynamic scoring forum at TaxVox, the blog of the Tax Policy Center.

Spin Alert: DOE Loans Are Losing Money, Not Making Profits

The Department of Energy snookered the media last week with a report that seems to show that its clean energy lending programs are profitable. “Remember Solyndra? Those loans are making money,” went a typical headline.

Unfortunately, that’s not true. Taxpayers are losing money on DOE lending. Less than originally expected, and less than you would expect given media coverage of Solyndra, Fisker, and a few other failed loans. But smaller losses are still losses, not profits.

To understand DOE’s spin, consider a simple example. Suppose your spouse borrows $10,000 from a bank at 5 percent interest over 10 years so that you can lend it to your friend Bob on the same terms.

Everything goes well in the first year. Bob pays you, and your spouse pays the bank.

If your aunt asks how the deal is going, what would you say? A good answer would be, “We are breaking even; let’s hope Bob keeps paying us back.” You and your spouse are in this together, the loans from the bank and to Bob offset one another, and your best hope is for that to continue.

If DOE were asked, however, it apparently would say, “Things are great; Bob paid me $500 in interest, and I am on track to earn $5,000.” DOE takes credit for the interest that companies pay on their loans, but it doesn’t subtract—or even report—the interest costs that taxpayers pay to finance those loans. That’s like claiming profits on your loan to Bob, while ignoring the interest your spouse pays the bank.

DOE’s report does not address this issue, except in a footnote in a table (cut and pasted above) revealing that its $810 million of “interest earned” was “calculated without respect to Treasury’s borrowing cost.” In other words, DOE reports gross interest received, not the net interest taxpayers have earned after subtracting Treasury borrowing costs. The incomplete figures in the table seem to suggest that DOE has eked out a $30 million profit on its lending ($810 million in interest less $780 million in loan losses). But when we account for Treasury borrowing costs, taxpayers are actually well behind.

The report does not allow us to say just how far behind. We do know, however, that DOE loans are typically made at small, sometimes zero, spreads above Treasury rates. So a large portion of DOE’s “interest earned” must have been offset by borrowing costs. That puts taxpayer losses in the hundreds of millions of dollars.

The same concern applies to DOE’s statement that interest payments on these loans will eventually top $5 billion. Some media outlets are reporting that as $5 billion of profit. It’s not. That $5 billion does not include the cost of Treasury financing or of any defaults. DOE’s $5 billion figure is like claiming your loan to Bob is scheduled to bring in $5,000 in interest; it’s technically true, but tells you nothing about profits. Indeed, the Obama administration still predicts that DOE’s loans will lose money over their lifetimes.

DOE’s lending programs should not be evaluated solely or even primarily based on their profitability or lack thereof. What matters is their overall social impact. How much are they advancing new technologies? How much are they reducing future pollution? Have they created jobs and economic growth? And are any gains worth the taxpayer subsidies? Those are the questions we should be trying to answer.

If DOE wants to play the profitability card, however, it should do so in an accurate and transparent way. Last week’s report falls woefully short. DOE owes taxpayers an honest accounting of the financial performance of its lending programs.

P.S. In recent work, I raised concerns about how the government budgets for lending programs. One issue is whether we should measure profitability against Treasury borrowing rates (as currently done) or against market rates (which the government could earn by unsubsidized lending). I expected that issue to arise in DOE’s accounting. Instead, the agency ignored the cost of capital entirely. Budget policymakers eliminated that ploy more than two decades ago, so it is stunning DOE would resurrect it.

A “Normal” Budget Isn’t Really Normal

Treasury closed the financial books on fiscal 2014 last week. As my colleague Howard Gleckman noted, the top line figures all came in close to their 40-year averages. The $483 billion deficit was about 2.8 percent of gross domestic product, for example, slightly below the 3.2 percent average of the past four decades. Tax revenues clocked in at 17.5 percent of GDP, a smidgen above their 17.3 percent 40-year average. And spending was 20.3 percent, a bit below its 20.5 percent average.

Taxes, spending, and deficits thus appear to be back to “normal.” If anything, fiscal policy in 2014 was slightly tighter than the average of the past four decades.

That’s all true, as a matter of arithmetic. But should we use the past 40 years as a benchmark for normal budget policy?

It’s common to do so. The Congressional Budget Office often reports 40-year averages to help put budget figures in context. I’ve invoked 40-year averages as much as anyone.

But what has been the result of that “normal” policy? From 1975 to today, the federal debt swelled from less than 25 percent of GDP to more than 70 percent. I don’t think many people would view that as normal. Or maybe it is normal, but not in a good way.

Just before the Great Recession, the federal debt was only 35 percent of GDP. Over the previous four decades (1968 through 2007), the deficit had averaged 2.3 percent of GDP, almost a percentage point lower than today’s 40-year average.

That comparison illustrates the problem with mechanically using 40-year averages as a benchmark for normal. A few extreme years can skew the figures. In 2007, we would have said deficits around 2 percent of GDP were normal. Today, the post-Great Recession average tempts us to think of 3 percent as normal. The Great Recession has similarly skewed up average spending (from 19.9 percent to 20.5 percent) and skewed down average taxes (from 17.6 percent to 17.3 percent).

As recent years demonstrate, we don’t want a normal budget every year. When the economy is weak, it makes sense for taxes to fall and spending and deficits to rise. When the economy is strong, deficits should come down, perhaps even disappear, through a mix of higher revenues and lower spending.

Looking over the business cycle, however, it is useful to have some budget benchmarks. A mechanical calculation of 40-year averages won’t serve. Instead, we need more objective benchmarks. On Twitter, Brad Delong suggested one benchmark for deficits: the level that would keep the debt-to-GDP ratio constant. I welcome other suggestions.

The $300 Billion Question: How Should Congress Budget for Federal Lending Programs?

Lending programs create special challenges for federal budgeting. So special, in fact, that the Congressional Budget Office estimates their budget effects two different ways. According to official budget rules, taxpayers will earn more than $200 billion over the next decade from new student loans, mortgage guarantees, and the Export-Import Bank. According to an alternative that CBO favors, taxpayers will lose more than $100 billion.

Those competing estimates pose a $300 billion question: Which budgeting approach is best?

As I document in a new report and policy brief, the answer is neither one. Each approach tells only part of the story. Congress would be better served by a new approach that fairly reflects all the fiscal effects of lending.

Compared with what?

If lending programs perform as CBO expects, they will bring in new money that the government can use to reduce the deficit, increase spending, or cut taxes. In that sense, taxpayers may come out more than $200 billion ahead.

But these programs do not fully compensate taxpayers for their financial risk. If the government took the same risk by making loans and guarantees at fair market rates—perhaps by investing in publicly traded bonds—taxpayers would make much more. Taxpayers are subsidizing the students, homeowners, and companies that borrow through these programs. In that sense, taxpayers come out more than $100 billion behind.

The same issue can arise in personal life. Suppose your aunt asks for a $10,000 loan to start a business. You’ve got exactly that much in a government bond fund earning 2.5 percent, and she offers to pay 5 percent. She’s got a good head for business, so the risk of default is very low; realistically you expect a 4 percent annual return.

The loan sounds like a winner, right? Her 4 percent beats the bond fund’s 2.5 percent, if you can handle the risk. But there’s one other thing: your brother-in-law, equally good at business, would like a similar loan, and he’s willing to pay 6 percent, with an expected net of 5 percent.

Now the loan to your aunt sounds like a loser. Your brother-in-law’s 5 percent beats her 4 percent. You might still prefer to lend to her, but you would come out behind in financial terms.

The competing CBO estimates reflect this dichotomy. One approach compares the financial returns of lending with doing nothing (the $200 billion gain in CBO’s case, 4 percent versus 2.5 percent in yours). The other compares the returns with taking similar risks and being fully compensated (the $100 billion loss in CBO’s case, 4 percent versus 5 percent in yours).

Both comparisons provide useful information. If you want to predict the government’s future fiscal condition, you should compare the financial returns of lending with doing nothing. If you want to measure the subsidies given to borrowers, you should compare returns with the fair market alternative.

When you discuss your aunt’s proposal with your spouse, you would be wise to mention not only the potential financial gain (“4 percent is better than 2.5 percent”) but the subsidy to your aunt (“4 percent is less than the 5 percent your brother would pay”). Only then can you have an open discussion of your family’s financial priorities.

Today’s approaches

The same information is necessary for an open discussion of federal budgeting. But official budget rules, created by the Federal Credit Reform Act of 1990 (FCRA), require CBO to use just the first approach in its budget analyses. Official estimates thus measure the fiscal effects of lending, not the subsidies provided to borrowers. CBO rightly believes, however, that policy deliberations are incomplete without measuring the subsidies, which CBO calculates separately using an approach known as fair value.

Policy analysts have vigorously debated the pros and cons of FCRA and fair value for years. Neither side has scored a decisive win for a simple reason: both approaches are incomplete. Fair value measures subsidies well, but tells us nothing about fiscal effects; this is its missing-money problem. FCRA measures lifetime fiscal effects well, but tells us nothing about subsidies.

By recording expected fiscal gains the moment a loan is made, moreover, FCRA makes lending appear to be a magic money machine. Lending may pay off over time, but the gains do not happen the moment the loan’s ink is dry. Like any lender, the government must be patient to earn those returns. It must hold the loan, perhaps for many years, and bear the associated financial risk.

A better approach

For those reasons, I believe we should replace both approaches with a more accurate budgeting method, which I call expected returns. As the report and brief describe, the expected-returns approach forecasts the fiscal effects of a loan by projecting the government’s expected returns year by year, rather than collapsing them into a single value at the time the loan is made, as both FCRA and fair value do.

Expected returns accurately tracks the fiscal effects of lending over time, thus avoiding both fair value’s missing-money problem and FCRA’s magic-money-machine problem. It also provides a natural framework for reporting the fiscal effects of lending and the subsidies to borrowers. Expected returns would give policymakers and the public a more accurate assessment of federal lending than either of the approaches we use now.