Energy taxes and economic growth in OECD countries: a simultaneous equations approach

ABSTRACT

This paper explores the channels through which energy taxes may affect economic growth, using a simultaneous equations model for a balanced panel data of 31 OECD countries over the 1994–2013 period. The empirical results reveal a negative impact of energy taxes on physical investment in the short and long term. This impact is negatively sensitive to the existence and level of public debt. Additionally, the results show that energy taxes have an indirect effect on human capital through their impact on polluting emissions. The taxes on energy products are able to reduce both the flux and the stock of polluting emissions that have a negative impact on human capital skills in the short and long term. Finally, we found that energy taxes could encourage eco-innovation in the short and long term.

KEYWORDS:

• Energy taxes
• economic growth
• public debt
• simultaneous equations model
• multiple imputation

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The energy taxes revenues data provided by OCED statistics cover the 1994–2014 period. But as the data on capital human are available only until 2013, we decided to restrict our study from 1994 to 2013.

2 According to Pigou (1920) the optimal environmental tax is the tax that equals between the marginal private benefit of emissions in production and the marginal social damage of emissions. While the international organizations define environmental tax as “a tax whose tax base is a physical unit (or a proxy of it) that has a proven specific negative impact on the environment” (United Nations et al. 2003).

3 Where $m>1$ is the number of imputations.

4 Note also that Redundant fixed effects lead to the rejection of estimations based on pooled equations in favour of fixed effects estimations. However, we were unable to perform Hausman Tests because estimation of simultaneous equations with random effects using CMP is still an intractable problem (Bartus and Roodman 2014). Although it may be subject to high sample dependence, an advantage of Fixed-effects (in comparison to random effects model) is that it produces unbiased estimations (Allison 2009). Finally, we should also note that the focus of our research is not on invariant variables (and therefore, random effects modelling has no clear advantage).

5 When the independent variable (the proxy of energy taxes) is measured in units, while the dependent variable (the investment) is measured in percent or in log transformation, the interpretation of the independent variable coefficient is as follows. One unit increase in the independent variable is associated with a (independent variable coefficient * 100) percent increase in the independent variable, whereas all other variables in the model remain constant. See: https://stats.idre.ucla.edu/sas/faq/how-can-i-interpret-log-transformed-variables-in-terms-of-percent-change-in-linear-regression/