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In 2021, Germany launched a national emissions trading system (ETS) in its road transport and housing sectors. This climate policy instrument aims at raising the cost burden of consumers of fossil fuels, the major source of carbon dioxide (CO2) emissions. A promising approach to secure public acceptance for such a carbon pricing would be to entirely reallocate the resulting "carbon" revenues to consumers. This article discusses three alternatives: a) a per-capita reallocation to private households, b) the reduction of electricity prices by, e.g., decreasing the electricity tax, as well as c) targeted financial aid for vulnerable consumers, such as increasing housing benefits. To estimate both the revenues originating from carbon pricing and the resulting emission savings, we employ a partial equilibrium approach that is based on price elasticity estimates on individual fossil fuel consumption from the empirical literature. Most effective with respect to alleviating the burden of poor households would be increasing housing benefits. While this measure would not require large monetary resources, we argue that the remaining revenues should be preferably employed to reduce Germany's electricity tax, which becomes more and more obsolete given the steadily increasing amount of electricity generated by renewable energy technologies. Alas, reimbursing "carbon" revenues to consumers in the form of an electricity tax cut or, alternatively, by per-capita transfers is not foreseen by the German government. Rather, carbon revenues are scheduled to support a large spectrum of policy measures, such as increasing the subsidies for the purchase of electric vehicles from 4 to 9 thousand euros and increasing the commuting allowance of a driving distance to work as of 20 kilometers to outweigh the higher costs of driving due to carbon pricing. Such measures hardly yield any environmental benefits and may even foster counterproductive behavior. Moreover, they tend to favor wealthy, rather than poor, households and are thus questionable from both an ecological and a social policy perspective. Instead, to sustain the currently wide acceptance of carbon pricing in Germany if carbon prices should rise substantially, which is indispensable for reaching the national emission reduction goals, it is critical that the government establishes measures to primarily favor poor households and alleviate their burden originating from carbon pricing. [ABSTRACT FROM AUTHOR]

Discrete-continuous models have become a common technique for addressing selectivity biases in data sets with endogenously partitioned observational units. Alternative two-stage approaches have been suggested by LEE (1983), DUBIN and MCFADDEN (1984), and DAHL (2002), all of which capture the first-stage discrete choice by the multinomial logit model, while the second-stage outcome equation is estimated using OLS. The nonlinearity introduced by the selection bias correction implies that the second-stage coefficients cannot be interpreted as marginal effects. Instead, the marginal effects are obtained using the estimates from both the first and second stages, a step that has been widely neglected in the applied literature. After deriving formulae for the marginal effects obtained from these selection correction approaches, we estimate a joint model of automobile ownership and distance driven to quantify the rebound effect, the behaviorally induced increase in driving that results from higher fuel economy. Our example illustrates that the pattern of rebound effects varies substantially depending on the method of selection bias correction. [ABSTRACT FROM AUTHOR]