The benefits of action on implementing carbon taxation in Ireland: a demand system approach

Abstract

We employ the Affine Stone Index demand system and Irish data to quantify the distributional effects of additional carbon taxes, taking into account the monetary benefits of action. We estimated the avoided economic damages from climate change, and the monetary value of the avoided emissions using willingness to pay from the literature. When these benefits of action are included in the metric for tax incidence, the tax burden decreases considerably. In addition, when the benefits disproportionately benefit low income households, carbon taxes are no longer regressive. We also analyze a flat and a pro-poor revenue allocation. We found that while these instruments reduce vertical inequalities (i.e. across income levels), they can increase horizontal inequalities (within income levels). We show that these instruments can reduce the environmental savings attributed to the additional carbon tax. However, this problem can be minimized by a partial allocation of additional revenues.

Keywords:

• Household energy demand
• energy taxes
• microsimulation
• demand system

JEL codes:

• H23
• H31
• Q58

Acknowledgements

Tovar Reaños and Lynch acknowledge funding from the ESRI’s Energy Policy Research Centre.

Disclosure statement

There is no financial interest or benefit arising from the direct applications of our research.

Data availability statement

All the data used in this research is available upon application from the Irish Social Science Data Archive.

Notes

1 See World Bank (2021). Available at: https://www.carbonpricingleadership.org

2 see IGEES (2019). Available at https://assets.gov.ie/19749/77936e6f1cb144d68c1553c3f9ddb197.pdf

3 Note that $\text{log}\hspace{0.17em}(x)=\hspace{0.17em}\text{log}\hspace{0.17em}\left[C(p,y)\right].$

4 The authors approximate y by using $\text{log}\hspace{0.17em}(x)-\sum _i\overline{w_i}\hspace{0.17em}\text{log}\hspace{0.17em}(p_i)$, where $\overline{w_i}$ is the mean of the budget share.

5 Note that this definition is distinct from an unrelated definition of “equivalent income” that appears elsewhere in the economic literature, namely that of a measure of income by a household member that accounts for household composition and economies of scale.

6 Emission factors are available at https://www.seai.ie/resources/publications/Energy-Emissions-2017-Final.pdf

7 We estimate WTP for the second and fourth quartiles by assuming an elasticity of WTP with respect to income of 1. We also estimate the ratio of the mean income for the second quartile and the first one, and the ratio between the third and fourth one. We use data from the HBS.

8 These values are available at: https://www.cso.ie/en/index.html

9 See https://www.cso.ie/en/methods/housingandhouseholds/householdbudgetsurvey/

10 Note that the shaded area in the figure is the confidence band.

11 Parameters for socioeconomic variables are available upon request.

12 Cross price elasticities are also provided in Appendix.

13 In our sample in 2016, 85% of agricultural workers live in rural areas.

14 This metric is estimated by the ratio of the standard deviation and the sample mean.