Institute scholar Ernie Goss posted an interesting piece at the Economic Trends blog, which can be found here http://www.economictrends.blogspot.com/. In this post, “Taxing Rich More Heavily Gets Votes, But Ineffective in Reducing Inequality”, Dr. Goss discusses data involving the share of federal income taxes born by the top 10 percent of earners. It may not surprise you that the relative tax burden (measured by the share of income tax collections) born by that group has increased over time, while the share born by the bottom 50% has gone down. As Dr. Goss reports, many in the bottom 50% have negative tax rates, due to the Earned Income Credit and other refundable credits that function as transfer payments from the government.
Looking at the IRS Statistics of Income, it appears that this trend can be confirmed over a slightly larger time frame. (See SOI Bulletin Article – Individual Income Tax Rates and Tax Shares, Table 5, 1986-2009). Between 1986 and 2009, the share of Adjusted Gross Income (i.e., the bottom line on the first page of your Form 1040) for the top 10 percent has increased from 35 percent to 43 percent, reaching a peak of 48 percent in 2007. But that group’s share of total income tax has increased, too, from 54 percent in 1986 to 70 percent in 2009. Perhaps more telling is the fact that the top 50 percent accounts for 97.75 percent of individual income tax in 2009, up modestly from 93.54 percent in 1986.
As Dr. Goss points out, some politicians (and it should be added, academic elites, too) are making political points on the growing rate of income inequality. Their prescriptions involve even higher taxes for the “rich”, but these historical trends indicate that tax policies are not moving the needle toward greater income equality. This is a fair point.
And of course, there is much more to discuss here. Several questions come to mind, including: What should income equality look like? When will we know that we have achieved this putative good?
To think this through, let’s consider equality in a different context. How about death, instead of taxes? The Center for Disease Controls tracks deaths from various causes. See CDC, Table 12, Number of deaths from 113 selected causes (2013), available at http://www.cdc.gov/nchs/data/nvsr/nvsr64/nvsr64_02.pdf . CDC data is based on death certificate records, which may not track all causes quite adequately. For example, a 2013 study published in the Journal of Patient Safety indicates that hospital errors caused 440,000 deaths in 2013, which would be the third highest cause after heart disease and cancer according to CDC tallies.
Death reaches all of us at some point, but deaths are also distributed unequally, at different ages and from different causes. For example, motor vehicle transportation accidents caused 35,369 deaths, far less than heart disease or cancer. Accidental discharge of firearms caused 505 deaths, far less than drowning (3,391), homicide (16,121), or suicide (41,149). All of these outcomes fall below the estimate of deaths caused by medical errors in hospitals. Within each category, variation occurs based on age and demographic groups. More males die in motor vehicle accidents than females; there are racial differences as well.
Death strikes unequally. But should we expect otherwise? How can we judge these outcomes? Looking at numbers without thinking about the complexities behind the causes could lead to odd conclusions indeed. One might argue that incompetent medical professionals present a greater death risk than criminals or riding in cars, but this will not deter me from driving to the hospital if I need to, even if the hospital is in a bad part of town. Moreover, one might use age or demographic differences as the basis for making various claims about racism, sexism or ageism. But before we form policies to address disparities, shouldn’t we consider biology, geography, genetics, and other factors, which might also explain the difference?
Isn’t the same true with income? Income is an effect or outcome that is produced by complex and interrelated factors. Before jumping on the equality bandwagon, we first need to define the target, which is no mean feat. When does income inequality present a problem? For example, is some inequality necessary to incentivize production? Does the reason for inequality matter?
Understanding why some people earn more than others could be extremely valuable in formulating what, if anything, to do about differences. If high earners are more productive than lower earners, is that an acceptable reason for inequality? What about age, experience, and training? What about marriage and family stability? What about workforce participation and commitment? And what about risk-taking, whether in employment or entrepreneurial efforts?
Policy options here are also fraught with danger. Should we focus on ways to raise productivity and earning capacity of the less productive, or to lower the returns for the more productive? Is growing the income pie better for all, even if that growth does not get distributed evenly?
Finding ways to increase productivity is a tall order. Redistribution (i.e., lowering returns for the more productive through forced exactions) is something governments are already quite good at. But we also know from history that this may not turn out so well.
More to come on this topic, and thanks to Dr. Goss for starting the conversation.
Edward Morse
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