House, Senate bills beat current tax policy but are far from perfect
Both the Senate and House Republicans have now spoken about their preferred tax reforms. The differences between them are relatively minor.
The Senate plan would cut the corporate rate a year later, permit no deductibility of state and local taxes, retain the current mortgage deduction, retain the estate tax — but double the exempt amount — retain seven tax brackets, cut the top rate from 39.6 to 38.5 percent, provide different and somewhat more relief for small business and maintain the medical expense deduction.
{mosads}The Senate bill will delay the economic response to the reform and, on balance, make the reform slightly more progressive. But whatever comprise bill emerges, it will not change the big picture — how investment will respond to the lower corporate tax rate and expensing provisions, how much wages will rise, how revenues will change and how the rich will fare compared to the poor.
I’ve been studying the evolving Republican tax plan using two analytical machines. The first is The Global Gaidar Model (GGM) — a 17-region, 90-period overlapping generations model (OLG) that combines all of the world’s economies into 17 regions. The model is particularly well suited to evaluating the economic response to the GOP plan.
The OLG model is economics’ bread-and-butter framework for understanding how economies respond to fiscal reforms, demographic change, technological progress, the pattern of net immigration and a host of other factors.
In 1979, U.C. Berkeley economist Alan Auerbach and I developed a computer algorithm for solving large-scale OLG models. The resulting Auerbach-Kotlikoff (AK) model has been used and is being used around the world to simulate policy reforms.
Indeed, the Joint Committee on Taxation (JCT), the Congressional Budget Office (CBO) and the Tax Policy Center (TPC) all use versions of the AK model to study the dynamic feedback effects of tax reforms.
The GGM is, no surprise, also an AK model. Its major difference with the JCT, CBO and TPC AK models involves the detailed modeling of the rest of the world, including the specification of region-specific marginal effective corporate income tax rates (METRs).
This is crucial for properly understanding the current placement of global capital, how global saving will evolve and how much of the world’s accumulated savings will be invested in the U.S. through time both in the absence and presence of the reform. The GGM is very carefully calibrated to the United Nations’ current and projected demographics and the IMF’s fiscal data.
So, what U.S. economic response does the GGM predict? The answer, depending on the year in question, is a 12-to-20-percent increase in the U.S. capital stock, a 3-to-5-percent increase in U.S. GDP, and a 4-to-7-percent increase in U.S. real wages. The expansion of the U.S. economy, particularly its wage base, makes the reform essentially revenue neutral.
These findings are at odds with the TPC’s dynamic simulation results, which measure the economic response as a weighted average of the responses when their model is run as a completely closed economy and as a small open economy.
The weight on the closed economy results is 60 percent. The U.S. is, however, neither a completely closed economy nor a small open economy. Instead, it’s a large open economy. I don’t believe one can arrive at a correct answer by averaging two clearly wrong answers. I also view the choice of weights as arbitrary.
I have not yet seen dynamic simulations from the JCT or CBO. The JCT has released static scores indicating respective deficits of $1.5 trillion and $1.7 trillion over the next decade. Any trillion-dollar deficit number sounds alarming.
But even $1.7 trillion is less than 1 percent of the next decade’s total projected nominal GDP. It’s also less than 1 percent of our nation’s current $200 trillion fiscal gap (the present value difference between all projected spending, including debt service, and all projected taxes).
This is not to suggest we take official deficits lightly. On the contrary, our country is flat broke due to all its implicit debts that successive Congresses and administrations have carefully kept off-the-books. If we have any regard for our children, we desperately need to address the fiscal gap via higher revenues and lower spending.
I’ve written a short book, called “You’re Hired,” indicating how best to restore fiscal solvency. My point in stressing the relative small size of the JCT’s static score is to provide intuition for why the GGM predicts no expansion in the official debt-to-GDP ratio from the reform. The model’s expansion of the tax base is large enough to cover the relatively small projected static deficit.
What about fiscal fairness? Here’s where the second of the two aforementioned analytical machines, called The Fiscal Analyzer (TFA), which I developed with Alan Auerbach and Darryl Koehler, is relevant.
The TFA’s approach to understanding inequality and fiscal progressivity is markedly different from the conventional approach, which focuses on the distribution of current income, measures progressivity in terms of the ratio of current taxes to current income and lumps together households of all ages. Unfortunately, the conventional approach to distributional analysis is not good enough for government work.
Not all households will die at the end of the current year. Instead, virtually all households will live for many years into the future during which they will pay net taxes (taxes net of benefits). Second, comparing 30- and 80-year-olds based on current-year net taxes gives 30-year-olds no credit for the net taxes they will pay in the future and gives 80-year-olds no credit for net taxes paid in the past.
Third, current income is not an appropriate proxy for the present value of remaining lifetime spending, which is economics’ best measure of welfare. Fourth, superrich households can have zero or even negative current income.
The Fiscal Analyzer measures inequality in remaining lifetime spending on a cohort-specific basis, and it assesses fiscal progressivity by comparing remaining lifetime net tax rates of rich and poor households within the same cohort.
Rich and poor references the level of remaining lifetime resources (net wealth plus human wealth). The TFA considers all major federal and state tax and benefit programs. In examining the House tax plan, I’ve run all household respondents to the Federal Reserve’s 2013 Survey of Consumer Finances through TFA.
So what is TFA’s verdict on the GOP tax plan, which I’ve run assuming a 5.5-percent higher level of real wages as indicated by the GGM simulation? To begin, it shows very little change in remaining lifetime spending inequality.
Take 40-year-olds: The richest 1 percent account for 11.9 percent of total cohort spending under current policy and 12.0 percent under the tax reform. The poorest quintile account for 6.6 percent of cohort spending now and 6.3 percent with the reform. The middle quintile’s spending share is 13.7 percent in both cases.
How about remaining lifetime net tax rates? They fall very little. The average remaining lifetime net tax rate of the top 1 percent rises from 32.0 percent to 32.6 percent. And the net tax rate for the poorest 20 percent rises from negative 58.2 percent to negative 53.4 percent.
But thanks to the increase in wages, all resource groups experience an increase in remaining lifetime spending ranging from 2.2 percent for the bottom quintile to 6.3 percent for the middle quintile to 7.1 percent for the top 1 percent. In short, everyone benefits from the plan with the middle class benefiting in percentage, but not absolute terms, by almost as much as the rich.
My bottom line? The GOP plan beats what we now have, but it’s miles from my preferred reform. Given our fiscal gap and degree of inequality, it should be modified to produce more revenue and improve progressivity. One move in that regard is lifting the ceiling on Social Security’s payroll tax.
Laurence J. Kotlikoff is a William Fairfield Warren professor at Boston University and a professor of economics at Boston University.
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