The taxes for various income. Introduction: Progressive tax rate: It is defined as the system wherein taxes increase as the income increases, wherein high-income taxpayers pay more taxes as compared to the low-income taxpayers. Regressive tax rate: It is defined as the system wherein the taxes decrease as the income increases, wherein high-income taxpayers pay fewer taxes as compared to low-income taxpayers Proportionate tax rate: It is defined as the system wherein a flat tax rate is charged to all taxpayers irrespective of the income earned by them. Marginal tax rate: The tax paid on an additional dollar of the income is termed as the Marginal tax rate. In other words, it is an incremental tax paid on the incremental income

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If GDP goes up by 1% and the investment component of GDPgoes up by more than 1%, how is the investment share ofGDP changing in absolute terms?▶ In economics, what else is expressed as relative percentagechanges?

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Chapter 3, Problem 3.10P

To determine

The taxes for various income.

Introduction:

Progressive tax rate: It is defined as the system wherein taxes increase as the income increases, wherein high-income taxpayers pay more taxes as compared to the low-income taxpayers.

Regressive tax rate: It is defined as the system wherein the taxes decrease as the income increases, wherein high-income taxpayers pay fewer taxes as compared to low-income taxpayers

Proportionate tax rate: It is defined as the system wherein a flat tax rate is charged to all taxpayers irrespective of the income earned by them.

Marginal tax rate: The tax paid on an additional dollar of the income is termed as the Marginal tax rate. In other words, it is an incremental tax paid on the incremental income

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If GDP goes up by 1% and the investment component of GDPgoes up by more than 1%, how is the investment share ofGDP changing in absolute terms?▶ In economics, what else is expressed as relative percentagechanges?

CEO Salary and Firm SalesWe can estimate a constant elasticity model relating CEO salary to firm sales. The data set is the same one used in Example 2.3, except we now relate salary to sales. Let sales be annual firm sales, measured in millions of dollars. A constant elasticity model is[2.45]ßßlog (salary) = ß0 + ß0log (sales) + u,where ß1 is the elasticity of salary with respect to sales. This model falls under the simple regression model by defining the dependent variable to be y = log(salary) and the independent variable to be x = log1sales2. Estimating this equation by OLS gives[2.46]log (salary)^=4.822 + 0.257 (sales) n = 209, R2 = 0.211.The coefficient of log(sales) is the estimated elasticity of salary with respect to sales. It implies that a 1% increase in firm sales increases CEO salary by about 0.257%—the usual interpretation of an elasticity.

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