Over the last decades, it has become apparent that the disparity between top income shares in the United States and the rest of the US earners has been growing despite the establishment of progressive taxation systems. Research indicates that the increase in this disparity is as a result of the use of false data. Nevertheless, entree to IRS personal income tax registers advances researchers’ aptitude to take note of the true nature of the U.S. income as well as inequality, particularly at the very top of the distribution. This paper puts the premise provided to the test authenticating the work done by Piketty and Saez in 2003.
In 2013, the then US president, Barak Obama, indicated that the income inequality disparity in the US had been on the increase. In his speech, he stated that “is most pronounced in our country and it challenges the very essence of who we are as a people” (Cilke 14). The statement was an unprecedented truth because the issue of income inequality has been a hot topic in the American economics for decades. Though a variety of policies such as the progressive tax system have been put in place to reduce income inequality, the gap between the top earners and the rest of the US labor force keeps increasing over time. According to Auten and Nicholas, the reason for these inconsistencies in income stems from the researchers that have been offering false positive results (34). A vast majority of US researches on income inequality trends are focused on family income data, a methodology that gives inaccurate figures. In 2003, Piketty and Saez fashioned an new way of reducing the errors that had caused previous researchers to present inaccurate data. This was attained using Internal Revenue Service (IRS) personal income tax record data in order to keep record with the income levees as well as trend within the different tax brackets in the country. This new methodology provided the two rescuers with a substantial advantages over survey-based data in reference to sample size, high response rates, as well as lower recall bias (Atkinson, Piketty, and Saez 7). In 2011, the three scholars conducted a study based on this hypothesis, and the data they presented on personal income tax return data was focused on the share of income held by top income groups and how it has changed over time. It indicated a high disparity, unlike previous data. Nevertheless, the study has never been authenticated to date.
- To authenticate Piketty and Saez hypothesis
- To analyze the disparities of data used in the researchers.
- To understand the actual situation in the Top Income Shares In United States
Income inequality has been a socio-economic issue in the US for a century. In 1915, four decades since the US economy overtook the UK’S as the world’s largest one, Willford I. King expressed concern over the fact that about 15% of the US income went to the rich 1% (Wolff and Ajit 13). Thomas Piketty, as well as Emmanuel Saez, indicated that the figure had gone up to 18% and not 15% as stipulated by Mr. Willford (14). Nevertheless, the data presented by Mr. Willford was enough for the government to introduce a progressive taxation system to reduce the income disparities then (Cilke 15). Unfortunately, efforts to introduce a progressive tax system in which the more an individual earns, the higher the taxes he or she pays failed to reduce the gap between the 1%, 10%, 20% and bottom 70% of the income earners. In a review of the taxation records Atkinson, Piketty, and Saez indicated that in most of the cases studying the gap between top earners and the rest of the population the data used was not coherent with certain regulations principle of which was ‘Income’ as defined by Haig-Simons (34). The estimates follow the procedures set by the tax laws, rather than a preferred definition of income as presented by Haig-Simons (35). Going through their report, one comes across the analogy of the prevailing income gap. It is impossible to reduce income inequality when the data used does not cover the entire range of ‘income,’ which is inclusive of items such as imputed rent, fringe employer benefits, or accruing capital gains, and losses (Larrimore, Jacob, and Splinter 67).
Researchers who employ the use of the IRS tax return data omit some non-taxable revenues that is not presented on the IRS tax form. Unless additional data is supplemented by additional information from other sources that indicate non-taxable data the results remain inaccurate. It is significant for top income share researchers to understand that during tax data studies taxable realized capital gains from accrued investment gains are usually not recorded on the tax forms. In doing so, most researchers do not only obtain inaccurate figures on capital gains that are untaxable but also fail to reflect the period when the said accrued capital gains were presented. Consequently, the use of taxable realized capital gains significantly changes the amounts as well as trends in the total income share owned by the top 1% in reference to the use of accrued capital gains figures. From the data presented it is evident that to find an accurate figure of ‘Total Taxable Income,’ there is need to find a clearer definition of income than the one that exists.
Different people have varying amounts of income. From the information presented by Atkinson, Piketty, and Saez, it is evident that the choice of income definition influences the income trends (34). This differentiation in income definition is a reason for the tax failure in reducing the inequality gap. Therefore, the underlying question is what is the most appropriate way to measure income? The conventional definition of income as derived from various economic literature is the total entry of resources that a person needs to meet he or she consumption costs during a financial period notwithstanding where, from whom, and the form it takes (Burkhauser, Shuaizhang Jenkins, and Larrimore (a) 45). This description of income is a derivative of the premise provided by Haig-Simons. It indicates that an individual’s yearly income is equivalent to their consumption along with any other net alteration of the said person’s net wealth in that year (Burkhauser, Shuaizhang Jenkins, and Larrimore (b) 21). With Haig-Simons income assumption in minds, it can be argued that income should be inclusive of any consumable resource in an individual’s financial year. Consequently, when calculating total revenues, a researcher ought to include before income tax cash in-kind employee reimbursements, as well as accrued capital gains.
In summation, according to Atkinson, Piketty, and Saez, the gap between the top-earning population increases on a yearly basis because the figures used tend to ignore significant aspects of nontaxable incomes (34). The reason for this is that most researchers relate to Haig-Simmons’s premise of total income, which is inclusive of before income tax cash, in-kind employee benefits, as well as accrued capital gains. In the instance researchers align their calculations with these figures it is likely that a true representation of the top earners’ actual earnings will be found.
The nature of the study indicates that a researcher should use personal income tax return data to find the true representation of a top earners income.
This paper is a literature review case study that is based on explaining the process of finding accurate figures that would indicate the gap between the top earners in the US and the low earners. This chapter focuses on providing empirical evidence of the issues explained in chapter 2
The data used in this study is secondary data from other studies conducted on the accuracies of data used in taxation and income gap equality. The data in question the study is used specifically for computing tax return income. This date includes
- Taxable and tax-exempt interest.
- Self-employment and small business income,
- Pension and retirement income.
- Unemployment income and Social Security income).
- Taxable realized capital gains.
- Federal income and payroll tax liabilities of tax filers.
Most researchers in such studies use administrative tax returns data. Nevertheless, the data does not take into consideration the number of non-filers or the total amount of income sources that are not documented in the IRS form by those who file their returns. The data used for this particular study considers the factors above and made the necessary adjustments as follows.
Not all individuals file their returns with the IRS. Piketty and Saez (2003) follow a premise that suggests approximations the total number of would-be U.S tax units on an annual basis as indicted by Census Bureau survey data to incorporate non-filers into the study uses. Additionally, the study takes into account the assumption that the market income of non-filers is 20% of the average filers annually. It should be noted that the second assumption does not offer the actual distribution of the individuals who do not file their returns with eh IRS considering Cilke’s (2014) indication that 80% of non-filers are in the bottom 90 earners in the US with an average income of below $50,000. Additionally, research by Smeeding and Jeffrey indicated that another large group of non-filers are under the age of 20-year-old (45).
To integrate revenue preceding in the tax return forms, it is obligatory to take into account all applicable data from the a variety of other administrative agencies such as, Federal Reserve Board’s Survey of Consumer Finances, IRS, as well as the Census Bureau’s March Current Population Survey. To incorporate the benefits of non-filer, the study makes a comparative analysis of the total social security payment outlays received by the social security administration and the total reported on tax forms by fillers. The result will indicate the residual non-filing population.
Cash and in-kind transitions are not accurately reported on the tax forms; but are only estimated by the taxable dataset using a statistical software generating CPS data, which is inaccurate in its measure. According to (Wolff and Ajit 42) due fat that software generated data does not offer tax units, it is hard to tax top earners. However, the study aims to create estimated tax units by using the Piketty and Saez percentile methodology. Essentially, each of the tax units identified will be assigned to a taxing unit in the IRS data in the same centile. When incorporating in-kind of incomes into specific tax units, this study takes into account the approach as presented by Burkhauser, Larrimore, and Simon (2012) and CBO (2016).
Probably, the most significant addition to tax data is the approximation of accrued capital gains for each tax bracket. Armour, Burkhauser, and Larrimore developed the best procedure for estimating accrued gains (34). The procedure assumes that capital gains are a result of the essential value of each asset recorded at the beginning of a financial period. Additionally, it indicates that the resulting wealth to the returns acquired is taxable a factor supported by Piketty, Saez, and Zucman (2016), Saez and Zucman (2016) (Auten, Gee, and Turner pp.125-127).
Chapter 4: Results
Figure 1: Top 1 percent income share for various income definitions, excluding capital gains
Figure 1 is a graphical representation of various income definitions, excluding capital gains. As indicated, one of the reasons as to why there is a differentiation in chargeable tax figures is due to the varied definition of income. The first set represents comprehensive income \ of inflow of resources with no capital gains. The second set represents tax return income with no capital gains. The last set represents income as presented by Piketty and Saez (2003) tax return market with no capital gains.
Figure 2: Top 1 Percent Income Share for Tax Return Income with and Without Realized Taxable Capital Gains
Figure 2. is a representation of three tax data sets. The first set in the tax return income with no capital gains. Most researchers use this set in identifying the total income tax taxable without conforming to Haig-Simons definition of income. The second set is that of researchers who use Haig-Simons definition of income but do not include returns from accrued capital gains. As indicated in chapter 3 there is a differentiation in findings in the instance a researcher fails to incorporate accrued capital gains as taxable income. The last set is that used by researchers who conform to Haig-Simons definition of income and incorporate accrued capital returns of the 1% tax unit as taxable income.
Figure 3: Top 1 percent income share for comprehensive income with various treatments of capital gains
Figure 3 shows comprehensive income with various treatments of capital gains. As mentioned, the incorporation of various capital gains provides a variation in comprehensive income. The graph includes four sets of all-inclusive income. The first set includes comprehensive income with no tax gains (as indicated in figure 2). The second one full income data incorporates taxable realized capital gains. The third set is inclusive income that includes accrued investments and business gains. The fourth set comprises comprehensive income, with the inclusion of accrued investments, business, and housing gains.
Form figure 1 it is evident that every definition of income offers a different figure of the 1% income levels. The data offered by comprehensive income is in reference to the comprehensive Haig-Simons income measure. The tax market income is as presented by Piketty and Saez 2003 and tax return income as perceived by another scholar. The difference between the quoted figures is significant. The first set represents comprehensive income in the inflow of resources with no capital gains recording 9% in 1989 and 11% in2013. The second set indicates tax return income with no capital gains recording 13% in 1989 and 16% in 2013. The last set signifies income as presented by Piketty and Saez (2003) tax return market with no capital gains recorded; 14% in 1989 and 18% in 2013. From the beginning of some researchers on income inequality, the figures used are incorrect a factor that leads to false positives. Therefore, it suggests a reason for the higher gap despite the progressive tax introduction. The actual figures and those used in the research have a differentiation of 5% in 1989 and 7% in 2013. From this figure, President Obama’s speech is not a claim but a fact. The Top Income Shares in the United States are increasing. Nevertheless, this figure is not accurate to its self.
In figure 2, while using Top 1 Percent Income Share for Tax Return Income with and Without Realized Taxable Capital Gains, the variation increases significantly. From figure 1 the Piketty and Saez (2003) tax return market income, no capital gains are the highest figure. However, in figure 2 the same amounts are at the very bottom. When the figure is incorporated into Tax return, income taxable realized capital gains the gap rose to 12% in 1989 and 16% in 2013. Nevertheless, when using Piketty and Saez (2003) tax return market income, taxable realized gains the figure reaches the highest figure of about 14.9% in 1989 and 20% in 2013. Nevertheless, Piketty and Saez (2003) tax return market income, with no gains is lower, recording an about 13% in 1989 and 17% in 2013. From this analysis, there is an additional differentiation of the Top 1 percent income share based on with and without realized taxable capital gains.
Considering the data in figure 1 and two it is evident that the difference in income definition and failure to include taxable capital gains result in a distorted figure. Indeed, the data used to indicate Top Income Shares in the United States through taxation in 1989 is 9% while in actuality the figure is 14.9%. Additionally, the same figure in 2013 indicates a differentiation of 9%. This is evidence of a false positive while using comprehensive income. However, as in chapter 2, there are different kinds of gains each causing a differentiation in taxation within the Top Income Shares in the United States. Figure 3, below shows that there exists gap on every gain on comprehensive income. Comprehensive income, no capital gains in 1989 indicates 9% while Comprehensive income, taxable realized capital gains indicates 11%; Comprehensive income, accrued investment and business gains indicates 14% and finally Comprehensive income, accrued investment, business, and housing gains 13.9%. It is evident that gains have a significant influence on income taxable. In 2013 Comprehensive income, no capital gains are 11% while Comprehensive income, taxable realized capital gains is 13%, comprehensive income, accrued investment, and business gains are 19% and finally, comprehensive income, accrued investment, business, and housing gains are 18.9%. The actual gap between the data this used in research and what should be used is 4.9% in 1989 and 8.9% in 2013
In summary from the study conducted, the actual data that is used by most researchers indicates 9% in Top 1 percent income share for comprehensive income in 1989 while the actual figure as indicated by (Piketty and Saez, 67) is 18.9%. In 2013, the same figures indicated 11% in Top 1 percent income share for comprehensive income 11% while the actual figure is 21.9%. From this study, it is apparent why the rich Top Income Shares In United States keep increasing the gap between their income and the rest of the bottom earners while claiming to pay more taxes.
The top earners in the US have been paying more taxes than the bottom earners for the last half a decade. However, the gap between these two clusters of earners in the US has been on a constant increase. The presented analysis provides a theoretical reason explaining the phenomenon indicating false figures in reference to the definition of income by many researchers; lack of identifying taxable gains as well as the influence of different gains on incomes. The paper provides an empirical study to authenticate all claims above concluding that the gap between the Top Income Shares in the United States increases due to false positive from incorrect data.
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