Thank you, Anna!

Thanks, Jorge!

Many thanks to @mokuhn.bsky.social , Pavel Brendler, @christian-bayer.bsky.social , and to everyone who supported me during the PhD and on the job market!

Many thanks to @mokuhn.bsky.social , Pavel Brendler, @christian-bayer.bsky.social, and to everyone who supported me during the PhD and on the job market!

Congratulations, Manuel!

A huge thank you to my advisors and everyone who supported me along the way! @mokuhn.bsky.social, Pavel Brendler, Christian Bayer @econtribute.bsky.social (8/8)

Finally, carbon taxes have sizeable general equilibrium effects on housing prices, increasing those of non-emitting houses by 5 percent, while decreasing those of carbon emitting houses by the same amount. (7/8)

This has important implications for the political support for these policies, as place-based transfers allow to set a higher carbon tax under the constraint that the policy is beneficial to a majority of households in both regions. (6/8)

In contrast, place-based transfers avoid this spatial redistribution without reducing the speed of the transition to clean technologies. (5/8)

I find that recycling carbon tax revenues as lump-sum transfers redistributes from rural to urban households. For a carbon tax of 300 Euros per ton, the difference in the present value of net transfers is 8,000 Euros. (4/8)

Second, it builds a quantitative spatial general equilibrium model to evaluate different policies of recycling carbon tax revenues in terms of their redistributive effects and their political support along the transition to clean technologies. (3/8)

First, it empirically identifies the spatial dimension between rural and urban households as important, because the average annual carbon footprint of rural households in Germany is 2.2 tons higher than that of urban households, around 12 percent of the average carbon footprint.

My JMP makes two contributions to the discussion on the distributional consequences of carbon taxes. (1/8)