Arttu Ahonen

Abstract: Incomplete information on the voter-level impacts of efficient reforms can undermine their political viability by preventing redistribution that would compensate anyone facing more costs than they are willing to pay. However, a policy maker that observes proxies for voters' costs and willingnesses to pay can approximate the ideal transfers, making more voters benefit in expectation. In this study, I develop a general framework for analyzing how a policy maker maximizing the expected number of voters that benefit from a reform would allocate transfers, how much they gain politically from using the information they have on the voters, and how much the voters' private information costs them. I consider the empirical application of carbon pricing, providing the first description of transfer allocations that would maximize expected support for it among self-interested voters. I estimate voter costs and preferences from novel data that links individual-level administrative records with a government-backed poll eliciting respondents' willingness to bear randomly varied personal costs to achieve a real world abatement goal. While I find that support for the climate target clearly responds to the cost it imposes on voters, voter heterogeneity is ultimately more driven by variation in willingness to pay for the policy, only 10% of which is captured by the rich set of voter characteristics I allow the policy maker to observe. This means that the cost of private information for the political viability of carbon pricing is large: the expected number of voters that benefit from optimally targeted transfers is always much closer to the benchmark of equal transfers than to the upper bound that could be achieved if it was also possible to target on unobserved voter characteristics. Maximizing expected beneficiaries also comes with a potentially large opportunity cost in terms of welfare, and leads to discriminatory transfer allocations. This follows from a fundamental tension between the political objective and welfare, as well as fairness: the voters likeliest to be on the margin between winning and losing are not necessarily most in need of the money, or equally distributed along protected classes such as gender.

Abstract: How do our past residential neighborhoods shape our current habits? We study this in the context of driving in Helsinki. We exploit granular data on the universe of cars and individual residential locations in Finland to show that variation in car ownership and vehicle kilometers driven are explained to a much greater extent by differences between individuals than between neighborhoods. Furthermore, the neighborhoods where individuals used to live when they were underage explain a substantial amount of the variation in kilometers driven between individuals, accounting for many times more of the total variation than their current neighborhoods. We also show that growing up in a neighborhood with high car ownership makes drivers likely to drive more today, even conditional on car ownership in their current residential location and their household's characteristics. These results are suggestive of the importance of neighborhood exposure during early formative years in helping form habits that persist across residential locations and across decades.

Abstract: Using detailed administrative data on all cars and residents in Finland, we analyze the distributional implications of Finnish motor fuel taxes both across and within income deciles. We measure fuel tax burdens as the share of household income spent on fuel taxes, and estimate household-level burdens using car-level data on odometer readings, fuel economy and car ownership. Finland has some of the highest fuel taxes in the world, allowing us to observe fuel consumption choices made in an environment with significant fuel costs. Contrary to common belief, we find that fuel taxes are not regressive among all households; instead, upper-middle income households bear the highest tax burdens. Fuel taxes are regressive only among the 67 percent of households that own a car, as car ownership is much less common in the lowest income deciles. Most of the variation in tax burdens, however, is found within rather than across income deciles. Differences across income deciles explain only 1.5 percent of the variation in fuel tax burdens. We find that households that are located outside city centers, have children, or include employed people face higher tax burdens within income deciles. While average fuel tax burdens across income deciles could easily be equalized by redistributing the tax revenue, the within-decile differences are nearly impossible to eliminate even with targeted transfers. This is because less than 50 percent of the overall variation in fuel taxes paid is explained by observable household characteristics.