Abstract This paper provides a method to measure the traditional Kaldor-Hicks notion of “economic efficiency” when taxes affect behavior. In contrast to traditional unweighted surplus, measuring efficiency requires weighting individual benefits (or surplus) by the marginal cost to the government of providing a $1 transfer at each income level. These weights correspond to the solution to the “inverse-optimum” program in the optimal tax literature: they are the social planning weights that would rationalize the status quo tax schedule as optimal. I estimate the weights using the universe of US income tax returns from 2012. The results suggest that measuring economic efficiency requires weighting surplus accruing to the poor roughly 1.5–2 times more than surplus accruing to the rich. This is because $1 of surplus to the poor can be turned into roughly $1.5–$2 of surplus to the rich by reducing the progressivity of the tax schedule. Following Kaldor and Hicks' original applications, I compare income distributions over time in the US and across countries. The results suggest US economic growth is 15–20% lower due to increased inequality than is suggested by changes in GDP. Because of its higher inequality, the U.S. is unable to replicate the income distribution of countries like Austria and the Netherlands, despite having higher national income per capita.

Willig (1976) argues that the change in consumer's surplus is often a good approximation to the willingness to pay for a price change: if the income elasticity of demand is small, or the price change is small, then the percentage error from using consumer's surplus is small. If the price of a good is random, then the change in expected consumer's surplus (ECS) equals a consumer's willingness to pay for a change in its distribution if and only if its demand is independent of income and the consumer is risk neutral. We ask how well the change in ECS approximates the willingness to pay if these conditions fail. We show that the difference between the change in ECS and willingness to pay is of higher order than the L1 distance between the price distributions if and only if the indirect utility function is additively separable in the price and income. If additively separability fails, then the percentage error from using ECS is unbounded for small distribution changes, and is always nonzero in the limit except for knife-edge cases. If, however, the distribution change is smooth on the space of random variables, and either the initial price is nonrandom or state-contingent payments are possible, then the change in ECS might approximate the willingness to pay well. Unfortunately, this smoothness condition necessarily fails in some important applications of ECS.

gain in welfare. If there are no mechanisms allowing compensation to be paid, then it is necessary to assign weights to particular individuals. One of Economic analysis of climate change uses economic tools and models to calculate the scale and distribution of damages caused by climate change. It can also give guidance for the best policies for mitigation and adaptation to climate change from an economic perspective. There are many economic models and frameworks. For example, in a cost–benefit analysis, the trade offs between climate change impa Standard cost–benefit analysis (CBA) has been applied to the problem of climate change. In a CBA framework, the negative and positive impacts associated with a given action are converted into monetary estimates. This is also referred to as a monetized cost–benefit framework. Various types of model can provide information for CBA, including energy-economy-environment models (process models) that study energy systems and their transitions. Some of these models may include a physical model of the climate. Computable General Equilibrium (CGE) structural models investigate effects of policies (including climate policies) on economic growth, trade, employment, and public revenues. However, most CBA analyses are produced using aggregate integrated assessment models. These aggregate-type IAMs are particularly designed for doing CBA of climate change. The CBA framework requires (1) the valuation of costs and benefits using willingness to pay (WTP) or willingness to accept (WTA) compensation as a measure of value, and (2) a criterion for accepting or rejecting proposals: For (1), in CBA where WTP/WTA is used, climate change impacts are aggregated into a monetary value, with environmental impacts converted into consumption equivalents, and risk accounted for using certainty equivalents. Values over time are then discounted to produce their equivalent present values. The valuation of costs and benefits of climate change can be controversial because some climate change impacts are difficult to assign a value to, e.g., ecosystems and human health. For (2), the standard criterion is the Kaldor–Hicks compensation principle. According to the compensation principle, so long as those benefiting from a particular project compensate the losers, and there is still something left over, then the result is an unambiguous gain in welfare. If there are no mechanisms allowing compensation to be paid, then it is necessary to assign weights to particular individuals. One of the mechanisms for compensation is impossible for this problem: mitigation might benefit future generations at the expense of current generations, but there is no way that future generations can compensate current…