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AbstractThe effective income tax function is useful and practical methodology to analyze the relationship between income and tax amounts. It includes the measures of tax progressivity, the maximum effective tax rate, and horizontal inequity. We statistically estimated the effective income tax function using the seven countries out of LIS datasets and Korean data. We also estimated the R-S index and the Kakwani index so as to test the consistency among these indexes.Our empirical results give us several implications. Four different indexes of tax progressivity reflect different aspects about the progressivity, implying that it requires policy planners to evaluate the income tax system with alternatives. The estimated maximum effective tax rate is usually less than or ve ry close to its maximum statutory marginal tax rate, except for Norway and Korea. It implies that the estimation of the effective tax function is of great use and significance to evaluate the charateristics of the income tax law. The mean squared error from the effective income tax function can be used to represent the degree of the horizontal inequity as a 'quick' measure.2
Energy is closely related to environmental risk. A rising fuel price in the 1970s had hurt consumers and caused disturbance to the natural environment. Households could not afford high imported energy prices and thus resorted to fuel wood. Land competed for fuel wood and agricultural crops, and thus high fuel prices strained the environment with respect to the use of land. If human health and safe housing were included in environmental risk, a high energy price would induce broader environmental risk. Households with limited income would not be able to use expensive fossil energy to warm their houses and would depend on only electric mats or blankets to keep warm. Such insufficient warming methods would not only threaten their health but would also worsen the condition of their houses. The abrupt increase in energy prices in 2007 and 2008 had significantly impacted environmental risk. It forced low income households to spend more on energy, leaving less for other expenditure segments, but had left high income households generally intact. This contrasting effect between different income groups had increased the sustainability of the energy risks at the high prices. This study shows how risks associated with the household economy have increased in response to the recent dramatic increases in energy prices. We develop a method for assessing risk by using the variance of ratios of energy expenditure to current income. We then examine how differently the economic change has increased risk across expenditure segments. We find energy expenditure as the biggest contributor to the risk. In addition, we illustrate how energy expenditure has changed the risk profile for each income group, with the first group (i.e., the lowest income group) experiencing the greatest increase. This group hurts the most during days of high energy prices.
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