Using IRS Income Tax Data The IRS method of measuring income inequality or poverty is fundamentally flawed because IRS income tax data is designed to help collect income and not to compile demographic data. Tax data generally do not account for the role of differences in age and cost of living and must be adjusted for these factors to be useful. Additionally, IRS taxable income itself is a poor measure of real income and does not include or is distorted by retirement and college funds, capital gains, and homeownership. . Say no to plagiarism. Get a Custom Essay on “Why Violent Video Games Should Not Be Banned”?Get an Original Essay One of the fundamental flaws of IRS tax data is that it is collected annually and evaluated based on these annual data, while individual income tax quality relative poverty and relative poverty span 50 tax years or more. Citing an article from taxfoundation.org, the article states: “An American earning the average adjusted gross income (AGI) for his or her age falls into all five AGI quintiles throughout his or her life. » This means that for the truly average taxpayer, the income quintile they fall into depends primarily on age and the income quintile measures become a measure of the age of the population rather than a measure of poverty. Students especially skew the data because they typically have low incomes, although they are more likely to have higher incomes than their peers who immediately joined the workforce. Additionally, the IRS only deals with pure income and does not take into account regional differences in cost of living. The example given in the article is the case of Oakland CA, which has a median income of $51,700, just below the national average of $53,000. Based on pure IRS taxable income, Oakland appears to be a middle-class city, but, when adjusted for cost of living, the average income is only $42,000. The article did an excellent job exposing the dangers of over-reliance on statistics and the limitations of economic thinking. However, I think there are other factors not mentioned in the article that contribute to the fuzziness of the data. For example, in the section on the imprecision of measuring non-wage income, black market income was not taken into account. There are several million undocumented/illegal immigrants in the United States who would not be included in IRS tax data and likely millions more paid in cash under the table and tax-free by their employers, and even more who derive their income from crime. , in the section on price and cost of living inequalities between regions, an interesting example of the laws of supply and demand. Citing an article from taxfoundation.org, the article states: "Economist Lyman Stone found that people actually move not to places with higher nominal incomes, but to places with adjusted incomes prices are higher. » This demonstrates the sum total of increased demand for cheaper products and the importance of price-adjusted income relative to gross income in individual decision-making. If we assume that Stone is correct, then, if a person has a choice between two jobs with the same salary, one in a high RPA area, the other in a low RPA area, individuals would tend to has.