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Why has Europe Become Environmentally Cleaner? Decomposing the Roles of Fiscal, Trade and Environmental Policies

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Abstract

This paper examines the role of fiscal policy, trade and energy taxes on environmental quality in Europe using disaggregated data at the monitoring station level for the 12 richest European countries spanning the period from 1995 to 2008. Our estimations show that fiscal policies and energy taxes are important determinants of pollution through various mechanisms. We find that increasing the share of fiscal spending in GDP and shifting the emphasis towards spending in public goods and against non-social subsidies significantly lower the concentrations of sulfur dioxide and ozone but not nitrogen dioxide. At the same time, energy taxes reduce nitrogen dioxide concentrations but have no effect on ozone and sulfur dioxide. Finally trade openness has a direct effect on sulfur dioxide but no effect on nitrogen dioxide or ozone. Our estimates account for time-varying unobserved heterogeneity.

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Notes

  1. Studies have focused for example on the effects of public expenditure level and composition on poverty reduction, income distribution and inequality (Kaplow 2006), unemployment (Fougère et al. 2000), education (Hanushek 2003), and many other areas.

  2. Exceptions are the theoretical models of Barman and Gupta (2010) and Gupta and Barman (2009) and López et al. (2011) which include a general equilibrium theoretical model and an empirical application.

  3. Gassebner et al. (2010) survey the literature and find that excluding OECD countries from the sample provides different results; specifically the relationship between GDP growth and pollution loses significance. This suggests that focusing on the richest countries of Europe could provide new insights about the relevance of fiscal policies, trade and energy taxes.

  4. We select these pollutants because their measurements are reliable and consistent over time, they have the largest number of observations available, they can be regulated, and accepted quality standards exist for them (EPA 2010).

  5. \(\hbox {O}_{3}\) is the product of the combination of Nitrogen Oxides (\(\hbox {NO}_x\)) and volatile organic compounds.

  6. An alternative method to control for time-varying unobservable variables is the so-called Added Controls Approach which sequentially introduces a large number of controls (Altonji et al. 2005). Nevertheless, Altonji et al. (2005) do caution about this methodology: “....[it] is dangerous to infer too much about selection on the unobservables from selection on the observables if the observables are small in number and explanatory power or if they are unlikely to be representative of the full range of factors that determine an outcome”. (p. 182).

  7. Fiorito and Kollintzas (2004) provide a different but related taxonomy based on the relationship between the types of goods provided by the government and private consumption. Public goods are defined as those that cannot be provided by the private sector such as defense, public order and justice. Merit goods include health, education and others that are in part provided by the private sector but where the public sector may have an important complementary role.

  8. In addition, studies have shown that human capital investments often have spillovers that increase their social value beyond their private returns (Blundell et al. 1999; Fleisher et al. 2010).

  9. Given that the output elasticities of energy (or electricity) range from 0.3 to 1.35 for OECD countries (Adeyemi and Hunt 2007; Liu 2004; Olund 2010), macroeconomic policies such as fiscal spending may have an impact on production related pollution by affecting its sources such as output from electric utilities and industry.

  10. The fixed station characteristics \(\mathbf{X}_\mathbf{{ij}} \) vanish as a consequence of first differencing.

  11. The TVCE approach indeed follows the tradition of classical regression analysis of using prior information (or assumptions) as a means of economizing the number of parameters. For example, in pure cross-country regressions the full use of country effects would not allow estimating the effects of the (observed) variables of interest, and thus a common approach is to use regional effects instead of country effects. The prior information or assumption is that the countries within the region may have common unobserved effects.

  12. While our assumption that the unobserved time patterns can be fully captured by the \((T-2)\)th polynomial approximation is not certain, we can test whether the \(\mu _{jt} \) residuals (and therefore the \(\varepsilon _{ijt} \equiv \tilde{\varepsilon }_{ijt} +\mu _{jt} \) error term) are time-independent. If the hypothesis that the residuals are time-independent is not rejected, then the \((T-2)\)th order polynomial approximation may be sufficient to uncover the full time pattern of omitted variable effects on the endogenous variable. Hence, the TVCE approach would be effective in mitigating time-varying country-idiosyncratic biases caused by omitted variables. By contrast, rejection of the hypothesis of time-independent residuals would suggest that the effects of omitted variables are not fully controlled for.

  13. The inclusion of the FCE in regressions in differences has often been used in literature examining the determinants of economic growth (defined as log difference of per capita GDP), in which FCE are used to

    control for unobserved time-invariant country specific characteristics (see for example, Fölster and Henrekson 2001; Afonso and Furceri 2010).

  14. If country effect in the level equation is \(b_{00j}+b_{0j} \tau \) then by first differencing the regression, the level FE (\(b_{00j})\) vanishes and the FCE applying to differences becomes \(b_{0j}\).

  15. This classification, organizes government expenditures in ten general categories, according to their objectives or purposes, which is of the government’s administrative or organizational structure. The categories are: (i) general public services, (ii) defense, (iii) public order and safety, (iv) economic affairs, (v) environmental protection, (vi) housing and community amenities, (vii) health, (viii) recreation, culture and religion, (ix) education and (x) social protection (Jacobs et al. 2009).

  16. We control for heating degree days in our estimation, but are unable to account for cooling degree days due to lack of data. However, this omission may not be so serious given that most countries in our sample have only small windows of time in the summer when air conditioners may be used, and even then their incidence is low. In contrast, heaters are used more intensively in the winters.

  17. The standard errors in all the estimates are robust to heteroskedasticity and autocorrelation.

  18. Additionally, we test whether the residuals from the RSE-TVCE estimations are time independent by regressing them on a time trend \(\tau \) \((\varepsilon _{ijt} =constant+\beta \tau )\).The null hypothesis that the residuals are time

    independent is not rejected at any reasonable level for any of the pollutants; p values for the associated nulls are all above 0.99 (these results are available from the authors).

  19. Table C.1 in ESM Appendix C presents a summary of the analysis of the predicted values of the TVCE function. In most countries the effect of the omitted variables has been negative for \(\hbox {SO}_{2}\), and has changed sign over time for \(\hbox {NO}_{2}\) and \(\hbox {O}_3\). The majority of predicted values of the TVCE function are non-monotonic and have at least 2 turning points.

  20. These findings are consistent with the elasticity estimates in a few studies that have measured these effects. Millock and Nauges (2006) estimate elasticities of energy taxes on \(\hbox {NO}_2\) and \(\hbox {SO}_2\) that vary from \(-2.7\) to \(-0.2\) depending on the industry analyzed.

  21. One of the reasons energy taxes do not have a significant effect on \(\hbox {O}_3\) concentrations might be the nature of this pollutant since it is not emitted directly by any source and it is rather formed by the combination of certain precursor gases especially under hot and sunny weather conditions (EEA 2007). Another possible reason might be the positive effect of energy taxes over the participation of diesel vehicles on the automobile fleet (data that is not available for all countries and time periods); diesel vehicles tend to emit three times more ozone-precursor gases than gasoline vehicles. Vestreng et al. (2008) has shown that this is true in the countries where systematic data on the participation of diesel vehicles are available.

  22. The results for the Fixed Monitoring Stations Effects with Time Varying Country Effects (FSE-TVCE) alongside alternative specifications are available from the authors.

  23. It is worth noting that Italy includes a large number of observations, more than 1,500 observations or about 8 % of the total. This does not necessarily indicate a lack of robustness of the estimators; it is indeed remarkable that the coefficients are robust to the exclusion of all other countries even if dropping individual countries often entails removing 7 % or more of the total observations.

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Authors and Affiliations

  1. University of Maryland, 3125 Symons Hall, College Park, MD, 20740, USA

    Ramón López

  2. Department of Economics, University of Chile, Santiago, Chile

    Ramón López

  3. University of Maryland, 3103 Symons Hall, College Park, MD, 20740, USA

    Amparo Palacios

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  1. Ramón López
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  2. Amparo Palacios
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Correspondence to Amparo Palacios.

Additional information

This research was part of GRASP-CEPR research project funded by the European Commission titled “Growth and Sustainability Policies for Europe” (Ref. SSH-CT-2009-244725). The authors thank Antonio Estache, Asif Islam, Kabir Malik, Michael Settels and two anonymous reviewers for very helpful comments.

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López, R., Palacios, A. Why has Europe Become Environmentally Cleaner? Decomposing the Roles of Fiscal, Trade and Environmental Policies. Environ Resource Econ 58, 91–108 (2014). https://doi.org/10.1007/s10640-013-9692-5

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