To the dumb bastards that run our country, and especially Traitor Boehner...
The following is a collegiate level research paper done by me and two others, for which we aced the course in Intermediate Macroeconomics at a private college (not infected by the ignorant indoctrination of public universities, making their degrees worthless).
In short, we keep having to prove that cutting taxes increases revenues, while raising taxes decreases revenues, making Obama's arguments completely false and vicious lies. Instead, you are playing into his hands to rewrite history, and put in the history books on his presidency that, (say with Idiotocracy Neandrathal voice) "tax cuts bad; raising taxes good." Nothing could be further from the truth. We are already operating in the prohibitive range on taxes; therefore, raising taxes will destroy economic activity, causing a drop in revenues, not an increase. It will also cause more unemployment, more government dependency, and it will be worse for the middle class. The rich will take care of themselves. The dirty little secret is, it will also destroy the (already limited) opportunities that regular folks have at upward mobility. Graduated taxation doesn't exactly hurt the rich, but removes the opportunities for the rest of us to accrue wealth. This is why it is very very stupid for anyone who is poor to middle class to favor taxing the rich. What kind of person thinks that by hurting employers he will find success? All he will find is job loss as employers seek to cut costs, and higher prices as employers pass on excess tax costs to their customers, which will now include Obamacare costs. In the end, we all pay for it.
Laffer Curve paper below... (Yeah, you'll have to read the whole thing to get anything out of it.)
Paul D. Peterson
ECON 335, MW 10:30am
Term Paper 4/26/06
WHAT IS THE LAFFER CURVE?
It has long been debated what effect tax cuts have on government revenue, which casts ambiguity on what action governments should take in regard to tax policy. Economist Arthur Laffer advanced and promoted what is now known as the Laffer Curve (hereinafter referred to as `the Curve'), an economic theory which supposes that for a given economy there is an optimal income tax level to maximize tax revenues. If the income tax rate is set below this level, raising taxes will increase tax revenue, and if the income tax rate is set above it, then lowering taxes will increase tax revenue. Although the theory claims that there is a single maximum and that the further you move in either direction from this point the lower the revenues will be, this is only an approximation.1
Let us demonstrate the theory by evaluating the two extremes of the curve. At one end, there is a zero tax rate, which obviously means there is zero tax revenue. At the other end the tax rate would be 100% and people would have no incentive to work; therefore, there would also be no tax revenue. 2
Although the curve is usually drawn out as a symmetrical half oval with the peak being exactly halfway between zero and 100%, this peak point could be anywhere between zero and the 100 percentile and may not be anywhere near 50%. The practical question becomes one of where is our tax policy on the Curve before a proper decision can be made to changes in tax rates. If we are taxed in the prohibitive range on the graph below, which we believe is the case, lowering taxes will increase tax revenue.
The term "Laffer Curve" was reportedly coined by Jude Wanniski, a writer for the Wall Street Journal after a 1974 afternoon meeting between Laffer, Wanniski, Dick Cheney, and his deputy press secretary Grace-Marie Arnett. Mr. Laffer actually attributes this concept to an Islamic scholar by the name of Ibn Khaldun and John Maynard Keynes.
Statement of Hypothesis: The Laffer Curve Theory of reduced taxation is a valid theory, the application of which will increase overall tax revenues and benefit an economy by the stimulation of growth in the short to medium run, provided that taxation is in the prohibitive range shown on the graph above. Tax cuts at all income levels, but especially the upper tax bracket where businesses operate, has the greatest impact on disposable income, tax revenues and the economy as a whole. This recognizes that lower tax rates stimulate macroeconomic variables, such as work, output and employment.
Changes in tax rates have two effects on tax revenue. The first is called the arithmetic effect, which implies a direct relationship between tax rates and revenue. When tax rates go up, more taxes are collected, and revenue also goes up, assuming that output remains unchanged. Conversely, when tax rates go down, less taxes are collected and revenues go down under this effect. The second effect is called the economic effect, which implies an inverse relationship between tax rates and revenue. Simply put, when tax rates go down, economic factors are stimulated by providing incentives to increase such activities as, consumption, investment, output and employment, increasing the tax base. Raising taxes has the opposite effect by penalizing the engagement of these activities, retarding the economy. The economic effect prevails when taxation is in the prohibitive range, whereby a reduction in tax rates increases revenue. The economic activity produced by such a tax cut more than pays for the tax cut itself, that is, overpowers the arithmetic effect.
Therefore, the theory of the Laffer Curve is substantiated when the projected benefits to the economy come true in the short run, i.e., by the next year, which is normally the case. The theory predicts that the benefits of lowering taxes will improve consumption and investment, increasing output and the growth of businesses, increasing employment and growing the tax base, thereby increasing revenue. Certainly in the medium to long run, such stimulation becomes more and more evident.
Even though there are many factors impacting the amount of revenue collected by governments, such as, time period being considered, ease of movement into underground (or illegal) activities, the prevalence of legal and accounting-driven tax loopholes, and the tax system in place, and that the Curve does not itself predict whether a specific action of raising or lowering taxes will raise or lower revenues; the question becomes a relative one of where taxation falls on the Curve before a change is made. While some of these factors are practically immeasurable, tax cuts have the greatest impact, overpowering the others for any existing tax system. We postulate that the US tax rates have normally been in the prohibitive range. If this is true, the data will show that the Curve theory works in every case of cutting taxes. Such findings should be a principle that can be applied to any modern economy.
Our research takes data from the Federal Reserve Bank's database for tax revenues from 1929 to 2005. The changes in revenue for those years have been paired with the tax rates3 and the Fed's GDP figures from those years. For our study, the tax revenue is the dependent variable, and the tax rates and GDP are the independent variables. These years include the Kennedy tax cut of 1964, the Reagan tax cuts in the 1980's, and the tax cuts of President Bush during the first half of the current decade. We did a regression analysis of the data as presented above with the following results.
Adj R Square = 0.938187643 | Tax Rate-Rev Var t-stat = -3.05044553 | GDP-Tax Rev Var t-stat = 22.484488
The regression model strongly supports our hypothesis and assertions. The evidence strongly confirms the theory of the Laffer Curve. In the resulting data above, the "R Square" statistic represents how much of the variation of the result in the dependent variable is explained by the variation in the independent variables (tax rates and GDP), that is, how strong is their correlation with the dependent variable (tax revenue). This study shows a 93.8% "adjusted R-square" correlation, so on that basis, the Laffer Curve has been proven as a function of actual historic taxation policies and the resulting measurable effects. The "t-stat" figure measures the significance of the relationship between the variables in terms of how reliably predicted it is as a direct or inverse relationship, so long as it is a figure beyond the range of -2 to +2. Negative numbers show inverse relationships and positive ones show direct relationships. The t-stat for the relationship of tax rates to tax revenue (X Variable 1) shows a -3.05 statistical significance, showing an inverse relationship, which is what was predicted. The t-stat for the relationship of GDP to tax revenue shows +22.48, an even stronger statistical significance, showing a strong direct relationship, also predicted by the economic and arithmetic effects of the theory.
But how significantly correlated is the probability that the actual data represents the relationships presented, that tax rates are inversely related to revenue and GDP is directly related to revenue? The Standard Error figure is the Standard Deviation from the Mean (average), a statistical variable used in normal distribution tests for significant correlation. This means that in a normal distribution of data, a bell curve is formed encompassing 95% of all possible data around the Mean, three Standard Deviations out from the Mean, in both positive and negative directions; so the smaller the Standard Error, the closer the sample data is around the Mean, better representing the correlations being sought or proven, demonstrating the probability of success. Normally, a hypothesis being tested will be tested in such a way as to check the probability of failure, which is the compliment to the probability of success, or the p-value of the normal distribution phenomenon. Statistical significance can be shown when the test shows a p-value of less than 0.05, or even better, less than 0.01 (meaning less than 1% of the time, the hypothesis fails). The p-value of our variables shows we do have a great amount of statistical significance proving our hypothesis as correct regarding tax rates' relation to tax revenues (X Variable 1). It shows that for only .32% of the time, our hypothesis fails, but that means, our hypothesis is successful 99.68% of the time! For the relationship of GDP to tax revenues (X Variable 2), the relationship is even stronger with a p-value near zero.
Let us apply our findings now to the writings of economist Arthur Laffer on the theory of the Curve. (All data quoted below will be in real terms, adjusted for inflation.) There have been 4 major tax cuts in modern U.S. history, the earliest dating back to 1919 with the Harding-Coolidge tax cuts. The top marginal rate was cut from 77%, stepped down to 25% by 1925. During the 4 years immediately before 1925, revenue was declining by an average of 9.2% annually. Over the 4 years after the tax cuts, revenue gained 0.1% per year.4 While this initial effect is not as pronounced as later in the 20th Century as to positive revenue increases, it stopped a declining trend in tax revenue. The economy responded strongly to the tax cuts with output nearly doubling and unemployment sharply falling until the Great Depression, increasing GDP drastically, and improving the average American's quality of life, a period referred to as the "Roaring Twenties" to this day. While this period is not included with the regression study above, due to lack of available empirical information, the results from this period coincide with our findings.
In 1964 President J.F. Kennedy implemented tax cuts, reducing the top marginal rate from a high of 91% down to 77%, and 70% by 1965. JFK believed in pro-growth, supply-side tax policy, which resulted in the following. During the 4 years before the tax cut, there was an average annual revenue growth of 3.3%. In the 4 years following the tax cut, the average annual revenue growth exploded to 8.6%. The economical effect ruled the day in that incentives to work, produce and invest led to real GDP growth increasing greatly during the years following the tax cut, driving the growth in tax revenue. More people worked, expanding the tax base, as predicted, and decreasing unemployment, reducing government expenditures.
In 1981 President Ronald Reagan signed into law the Economic Recovery Tax Act, which lowered the top marginal tax rates from 70% to 69% in 1982 to 50% in 1983. By 1987, the top marginal tax rate had dropped to 38%, and then 28% in 1988. During the 4 years before the tax cuts (1978 - 82), the economy grew at an annual rate of only 0.9% with an annual growth rate in tax revenue of -2.8%. In the 4 years following the tax cuts, the annual growth rate more than quadrupled to 4.8% with an annual growth rate in tax revenue of +2.7%! "Prior to the tax cut, the economy was choking on high inflation, high interest rates, and high unemployment. All 3 of these economic bellwethers dropped sharply after the tax cuts. The unemployment rate, which peaked at 9.7% in 1982, began a steady decline, reaching 7.0% by 1986 and 5.3% when Reagan left office in 1989."5 While such drop in top marginal rates (from 70% to 28% over the span of 9 years inclusive, 1980-88) was extremely controversial for the time, we are pleased to report with 20/20 hindsight that the total actual revenue collected by the government from taxpayers in this top bracket was higher than it was before the tax cut.5 The Laffer Curve is proven and justified; it has withstood the test of time!
The Bush tax cuts of recent years have been smaller than in previous periods, chiefly due to the fact that the rate in place was already lower at 40% and was stepped down through 39% to 35%, where it is currently. Mr. Bush is credited with shortening the span of the 2001 recession in the wake of the 9/11/2001 attack on the World Trade Center. This is further proof of the economic effects of the Curve in our own time.
As alluded to above, we conclude that our hypothesis is true, that the Laffer Curve Theory is a valid, proven fact, and operates properly as indicated by the Curve in the prohibitive range. We believe the historic tax policies have unequivocally been operating in the prohibitive range above the optimal taxation rate. This is why tax cuts have always resulted in greater tax revenue and economic stimulation every time it is tried. This begs the question as to where the optimal tax rate might be; however, there is no empirical data or evidence to indicate that we have yet reached this point. If the government has been taxing the populace above the optimal rate throughout history, there is no way to tell how low tax rates can be dropped to maximize tax revenues without actually going there. Therefore, we would recommend that governments systematically drop their tax rates until the results stop supporting an increase in tax revenue and GDP during the following 1-2 years. Until this happens, it can be stated with certainty that over taxation of the economy continues to be the current status quo. It can also be stated that since the Laffer Curve operates as theorized in the prohibitive range, it follows that it will operate below the optimal rate as theorized as well. Therefore, when rates are dropped to the point that it does not help increase revenue or stimulate GDP, the optimal rate of taxation will have been realized. It is incumbent on government to figure out where this point is and leave tax rates alone once achieved.