The Vertical and Horizontal Distributive Effects of Energy Taxes: A Case Study of a French Policy.

AuthorDouenne, Thomas
PositionCase study

    It is paradoxical that while environmental taxes are considered by economists as one of the most efficient instruments to deal with environmental problems, public support for carbon pricing remains low, as showcased by the recent protests against the carbon tax rise in France. Initiated in 2014 at 7[euro]/tC[O.sub.2], the French carbon tax was planned to gradually increase in order to reach 86.2[euro]/tC[O.sub.2] in 2022, and even higher levels in a near future. In November 2018, in a context of high oil prices, the protests of the Yellow Vests against the tax led to the abandonment of the increases initially scheduled. Since, the tax has remained at its 2018 level, 44.6[euro]/tC[O.sub.2]. Similarly, the additional increases initially planned for the diesel tax have been abandoned. As of today, the future of the French carbon tax remains deeply uncertain. The negative impact of the tax on households' purchasing power was certainly what contributed the most to public discontent. In particular, Yellow Vests appeared concerned with the disproportionate burden that taxes on energies could impose on low income households, and more specifically on those most dependent on fossil fuels such as rural and peri-urban households.

    The objective of this paper is to precisely characterize and quantify the distributive effects of French energy taxes. Based on TAXIPP, a micro-simulation model of taxation for French households (see Appendix A.2 for a description of the model), I evaluate French fiscal policy on energies between 2016 and 2018, i.e. the last evolution before the emergence of the protests. The policy essentially involved an increase in the carbon price on all energies except electricity--which was already subject to the European Union Emissions Trading Scheme. While numerous studies have already assessed the vertical distributive effects of energy taxes--i.e. distributive effects between households along the income dimension--this paper contributes to the literature by investigating their horizontal distributive effects--i.e. between households with similar incomes. In particular, it shows that while low-income households may on average gain from an environmental tax after revenue-recycling, some of them could suffer large losses. This result echoes concerns raised by the Yellow Vests that carbon taxation may have a disproportionate impact on certain categories of households, such as rural and peri-urban households, but not necessarily all poor people. Understanding and quantifying these phenomena is key to a better design for these policies, and thus to improve both the fairness and support for ambitious environmental policies.

    Several papers have investigated the distributive effects of energy taxes in France (e.g. Ruiz and Trannoy, 2008; Bureau, 2011; Berry, 2019). Yet, partly due to the lack of a comprehensive database, few works have jointly covered housing and transport, and existing studies all focus on vertical equity. To investigate these issues together, I created a novel dataset by matching the French transport survey (ENTD) and the consumer expenditures survey ("Budget de Famille", BdF). Using this new dataset, I micro-simulate fiscal policy on energies between 2016 and 2018. Given the relatively small scale of the tax, the use of micro-simulation is relevant as general equilibrium effects should play a limited role. As argued by Bourguignon and Spadaro (2006), these models are the best fit for a precise investigation of the distributive effects of policy changes, as they fully take into account households' heterogeneity. The model accounts for behavioral responses through heterogeneous price and income elasticities estimated using a Quadratic almost ideal demand system (QUAIDS, see Banks et al., 1997). I find that the median household reacts significantly to transport fuel prices with an uncompensated price elasticity around -0.45, and to a lesser extent to housing energy prices with an elasticity of -0.2. I also find that reactions are expected to be stronger for lower-income and less urban households.

    Elasticities are then translated into changes in quantities and greenhouse gas emissions. For a given technology, the short-run response to prices appears to have a limited impact on aggregate emissions. With respect to monetary effects, I compute effort rates and analyze how the tax burden is spread across income groups, before and after revenue recycling. The results confirm the findings of the literature, whereby energy taxes are regressive when effort rates are computed as a function of disposable income (e.g. Poterba, 1991; Metcalf, 1999; Grainger and Kolstad, 2010), but are almost not when total expenditures are instead used to measure standards of living (see Poterba, 1989; Metcalf, 1999; Flues and Thomas, 2015). Also, I find that the compensation mechanism proposed by the government and targeted towards low-income households does not solve regressivity. However, recycling the revenue left after this mechanism through homogeneous lump-sum transfers--a mechanism known as flat-recycling (e.g. West and Williams, 2004; Bento et al., 2009; Bureau, 2011; Williams et al., 2015)--would make the policy progressive.

    From the above conclusions, it might seem straightforward to improve the acceptability of energy taxes. However, in the recent literature authors have emphasized the importance of the horizontal distributive effects of these taxes, which could be a major deterrent against their implementation (Rausch et al., 2011; Pizer and Sexton, 2019; Cronin et al., 2019; Sallee, 2019). In this paper, I analyze the distribution of gains and losses within income groups. In particular, I show that after flat-recycling, over a third of low-income households are expected to lose out due to the policy. Additionally, 25% of households in the bottom income decile are expected to lose more than the median household in the top income decile. This result confirms that distributive effects are expected to be much larger in magnitude within income groups than across income groups, and could dampen the policy's acceptability.

    Important progress has recently been made by general equilibrium models to incorporate more heterogeneity in households' characteristics (e.g. Rausch et al., 2011; Rausch and Schwarz, 2016). Yet, it is still unclear what the drivers are of the heterogeneous incidence of energy taxes (Pizer and Sexton, 2019). The literature has mostly focused on geographical criteria, looking at the differentiated impact across regions, and has emphasized the role of income composition. Thanks to micro-simulation, I adopt a more agnostic approach to characterize the determinants of the tax incidence at the household level. Among many drivers, I show that the energy used and to a lesser extent the urban density of the household residence account for a large share of horizontal distributive effects. I illustrate this point by testing alternative scenarios for revenue-recycling using targeted transfers based on these characteristics. I find that indexing transfers on the urban density has no effect, while indexing them on the type of energy used for heating only slightly softens horizontal equity issues.

    This paper contributes to several strands of the literature. First, it uses statistical matching to build the most comprehensive existing database to study energy taxation in France. Using these data, it also offers an extensive evaluation of the most recent environmental fiscal policy. Second, this paper adds new evidence on the incidence of energy taxes with respect to both vertical and horizontal heterogeneity. In particular, it sheds new light on the importance of the latter and its implications for the acceptability of environmental taxes. It also goes further than previous studies by using micro-simulation to identify the determinants of this heterogeneity at a more precise level. Given the urgent need to implement ambitious environmental policies and in particular carbon pricing, it is crucial to better understand the concerns associated with these instruments. Only then will we be able to bring effective solutions to improve their acceptability.

    The paper is organized as follows. Section 2 presents the data, and section 3 the estimation of households' elasticities with respect to their energy consumption. Section 4 evaluates the expected environmental effects of the policy and distributive effects between income groups. Section 5 discusses distributive effects within income groups and highlights the determinants of the tax incidence in order to propose alternative revenue-recycling mechanisms. Section 6 concludes. Technical elements are reported in the appendix, and an online appendix adds supplementary material to describe the matching of household surveys.

  2. DATA

    2.1 The French household surveys

    A comprehensive study of the incidence of energy taxes on households must include both housing and transport energies. In France, energy consumption from the transport and residential sectors represents respectively 27% and 12% of total emissions. Yet, most studies on French data have ignored one of these sectors. Bureau (2011) studies the distributional impacts of a carbon tax followed by lump-sum transfers, but focuses on transport fuels only. Using "Budget de Famille" (BdF) survey data, Nichele and Robin (1995) cover both issues but they do not estimate elasticities specifically for energies, nor do they precisely detail the distributive effects of the tax. Closer to the present work, Berry (2019) investigates a previous increase in the carbon price on energies using the "Phebus" database. However, the smaller sample size and the limited quantity of information in this survey do not enable further exploration of the determinants of horizontal distributive effects.

    In this paper, I use the latest version of the "Budget de Famille" (BdF, 2011) consumer survey. Because of its very large...

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