Impacts of carbon pricing on income inequality in Brazil

Abstract

The introduction of a tax on greenhouse gases aims to increase awareness of the real costs of economic activities across all stakeholders. In the absence of such tax, these activities generate negative externalities, a market failure that imposes costs on others, including future generations. Developing countries have increasingly contributed to climate change, and emission mitigation policies are therefore also required in these economies. Among the priorities in their political agendas, however, are to reduce income concentration and alleviate poverty. Climate policies should therefore be implemented without interfering with such social goals. This study uses a Social Accounting Matrix for Brazil in 2005 to analyse the impact of implementing a charge per tonne of CO₂e emitted on income distribution in Brazil. The results differ as much in relation to the level of the applied tax as to the means whereby the revenue thus raised is recycled in the economy. Two option paths are simulated: direct transfer to low-income families and exemption from labour taxes. As complementary results, impacts on GDP, on employment levels, and on GHG emissions are also analysed.

Keywords:

• climate change
• mitigation
• Latin America
• economics

Notes

1. Acronym in Portuguese.

2. In addition to carbon taxes, there are other climate policy instruments, such as cap-and-trade, and command-and-control systems of pollution standards, for example. It was felt, however, that carbon taxes are the most appropriate tool for the analysis undertaken in this paper.

3. Baranzini et al. (2000) point to the possible existence of high administrative costs.

4. Acronym in Portuguese.

5. Acronym in Portuguese.

6. The value used is R$200.00 (two hundred Reais), the rate in effect on 15 January 2003, reference date of the research.

7. The calculation was carried out as follows:(1) where μ_c,i represents the share of class c in the total expenditure/income with item i in percentage terms, Q_c,i represents the total spent or received by the family in class c with item i, F_c represents the number of families belonging to the class c and Σ (Q_c,i * F_c) represents the sum of the total spent or received by all households in the economy with item i.

8. In the 2002–2003 POF, 85.3% of the families with the lowest incomes had, on average, expenditure in excess monthly receipts, and 68.4% with the lowest incomes were already in this situation in 2008–2009. Source: IBGE (2010a, 2010b).

9. There are effective economic policies to combat illegal logging, such as payment for environmental services and agricultural credit policies (see Assunção, Gandour, Rocha, & e Rocha, 2013). However, these policies do not apply to the model used.

10. The average exchange rate between Brazilian Reais and American Dollars in 2005 was R$/US$ 2.44 (Source: IPEAdata, 2014).

11. Although it is possible to simulate what would be the change of the VA_j numerator after applying the carbon tax, it would be difficult to do this for the variables L_j (employment) and C_j (GHG). For simulation purposes, the Y_jf denominator was therefore changed, adding the total amount of tax collected to the total original value.

12. In order to obtain more illustrative results, it was chosen to present the impacts of GHG emissions as ‘Avoided GHG emissions' and the impacts on income inequality as the inverse of the Gini coefficient. This way, positive variations in all variables analysed are desirable and negative variations are undesirable.

13. The exoneration of charges on labour helps to create more jobs and reduce levels of informality in the economy, which would benefit the lower income classes and possibly improve the distribution of income in the economy. However, these effects are difficult to obtain in a short-term static analysis.

14. Since these results only include an increase in GDP of 0.29% at the most, this limitation does not in fact undermine the model. It was, however, considered relevant to highlight it.

15. For a more detailed study of the effects of mitigation measures on the competitiveness of Brazilian industry, see Henriques Jr. (2010) and Rathmann (2012).