What would you expect to see in the frequency distribution of windows estimated from the data?

The window tax provides a dramatic and transparent historical example of the potential distorting ef Show more The window tax provides a dramatic and transparent historical example of the potential distorting effects of taxation. Imposed in England in 1696 the taxa kind of predecessor of the modern property taxwas levied on dwellings with the tax liability based on the number of windows. The tax led to efforts to reduce tax bills through such measures as the boarding up of windows and the construction of houses with very few windows. Sometimes whole floors of houses were windowless. In spite of the pernicious health and aesthetic effects and despite widespread protests the tax persisted for over a century and a half: it was finally repealed in 1851. A tax system creates a notch if a small change in behavior leads to a discrete change in both average and marginal tax rates. The window tax incorporated notches throughout much of its history. Consider the tax schedule over the 17471757 period. A person who owned a home with 9 or fewer windows paid no tax. But his neighbor whose home had 10 windows would pay a tax of 6 pence for each window. Consequently for the neighbor the marginal tax rate for the 10th window was 60 pence (which is equal to 5 shillings) while the average tax rate for the 10 windows was 6 pence. The window tax was unchanged from 1747 to 1757 and included three notches. A homeowner in this period paid no tax if the house had fewer than 10 windows; a tax of 6 pence per window if the house had 1014 windows; a tax of 9 pence per window if the home had 1519 windows; or a tax of 1 shilling per window if the home had 20 or more windows. Thus the marginal and average tax rate jumped sharply when a consumer installed the 10th 15th or 20th window. Source: Wallace E. Oates and Robert M. Schwab. The Window Tax: A Case Study in Excess Burden Journal of Economic Perspectives Volume 29 Number Winter 2015 Pages 163180. Suppose you have tax data on the window tax in this period. If the window tax distorted behavior What would you expect to see in the frequency distribution of windows estimated from the data? Show less

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