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The Impacts of Alternative Policy Instruments on Environmental Performance: A Firm Level Study of Temporary and Persistent Effects

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Abstract

Using a rich Norwegian panel data set that includes information about environmental regulations such as environmental taxes, non-tradable emission quotas and technology standards, all kinds of polluting emissions, and a large number of control variables, we analyze the effects of direct and indirect environmental regulations on environmental performance. We identify positive and significant effects of both direct and indirect policy instruments. Moreover, we test whether the two types of regulations lead to positive and persistent effects on environmental performance. We find evidence that direct regulations promote such effects. Indirect regulations, on the other hand, will only have potential persistent effects if environmental taxes are increasing over time.

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Notes

  1. Heine et al. (2012) is a recent contribution that summarizes principles and practices of environmental tax reforms that also includes administrative and direct regulations.

  2. For a flow pollutant or a uniform-mixed stock pollutant, Perman et al. (2011).

  3. See Martin et al. (2016) for a review of the empirical evidence for the EU ETS so far.

  4. Martin et al. (2014) finds a negative effect of the UK carbon tax on firms’ energy intensity. They do not, however, measure the effect on emission intensity or test for persistent effects.

  5. As economies have become richer, support has been found for the existence of an Environmental Kuznets Curve (EKC), which implies an inverse u-shaped relationship between emissions [even for green-house gas emissions, Cole et al. (2005)] and country income (GDP), Andreoni and Levinsohn (2001). There are different hypotheses for the existence of an EKC, but it is reasonable to believe that the growing environmental and political concern about regulating polluting emissions has contributed to this inverse u-shape. The contributions to this u-shaped curve can be decomposed into substitution-, technology-, and scale effects (Bruvoll and Medin 2003; Bruvoll et al. 2003; Bruvoll and Larsen 2004).

  6. The Shadow Prices handbook (de Bruin et al. 2010) is developed by CE Delft, an independent research and consultancy organization. The Handbook is available on the website of CE Delft. We use the damage estimates for a large proportion of the several hundred substances listed in Tables 50 (Damage costs for emissions to air) and 52 (Damage costs for emissions to water) in the Annexes to this report. The damage costs for emissions to air are obtained using NEEDS damage costs. The NEEDS project is an ExternErelated European study on the external costs of energy use. The damage costs for emissions to water are obtained using direct valuation of ReCiPe endpoint characterization factors. Since this method is less reliable than using NEEDS damage costs, damage estimates for emissions to water are only approximate.

  7. Norway is part of the European power market, but the exchange of power has been but minor in the estimation period.

  8. Law prohibiting harmful pollution: http://www.lovdata.no/all/nl-19810313-006.html.

  9. However, firms may underreport emissions. A potential source of bias related to self-reported emissions is if after an inspection, firms found in violation report emissions more correctly (i.e. an increase in the reported emissions). If this is the case, the effect of direct regulations would be underestimated.

  10. Féres and Reynaud (2012) measure formal regulations as the number of inspections and average efficiency of warnings and fines from the local environmental agencies. The only firm-level variable connected to direct regulations is a dummy variable that describes the license status of the firm.

  11. When inspecting plants, the NEA focuses on violations of procedures and general maintenance of equipment rather than on actual emissions (Telle 2004). The complete permits also contain a number of qualitative requirements concerning institutional, technological as well as formal aspects of the plant. The data on the firms’ violations probably provide a good overview of the compliance with the environmental regulations. Data on self-reported violations are also available, although we only use the violation status from the NEA inspections.

  12. We have also considered alternative measures of direct regulations such as e.g. dummies on introduced technology standards, dummies on technology regime changes, and inspection frequency. Introducing dummies on technology standards would involve severe heterogeneity problems with regards to timing as the standards are typically implemented several years after they are announced, and as several firms are granted extensions. Dummies on regime changes, as used by Popp (2003), will likely pick up on several effects other than the change in regulation. Moreover, dummies will neither capture the timing of the firm specific regulatory costs, the differences in regulatory costs across firms facing direct regulations, nor the effects of the many different technology standards that are implemented. Finally, inspection frequency is likely to capture the regulator’s conception of the risks associated with the firm’s emissions, and not just the regulatory costs. The inspection frequency varies with risk class. We thus prefer prefer controlling for risk class rather than including it in our measure of the regulation.

  13. Examples of possible factors are the likelihood that the firm will comply without sanctions being imposed, the ability of the firm to handle the requirement economically or practically, and finally, the risk class of the firm. The threats of sanctions tend to be more severe for the firm the higher is the risk class (the lower is R) and therefore we control for the risk class, see Sect. 4. Firms with e.g. low economic performance may receive lower fines, offsetting a possible bias for weak economic firms to be more prone to comply after the warning in order to avoid the fine.

  14. The period 2005–2007 was a pilot first phase for EU ETS in EU and Norway. See the EU’s quota directive (2003/87/EF) and European Environment Agency (2005). The oil and gas industry in Norway was not included in the first phase, but was included in the second from 2008. The processing industries, except for the aluminum industry, have been included since 2005; see also Ministry of the Environment (2011).

  15. Emissions of \(SO_{2}\) have been liable to environmental taxation since 1970, starting with a differentiated tax on mineral oils and extended to include a \(SO_{2}\)-tax on coke and coal in 1999. In 2002, this tax on coke and coal was replaced by a memorandum of understanding between the Ministry of the Environment and the Association for Processing industries. Taxes on HFC and PFC were introduced in 2003. The NOx-tax was introduced in 2007 on all NOx-emissions except those from the processing industry, combined with a NOx-fund for several industries (Hagem et al., 2012). A tax on the chemicals trichloroethene and tetrachloroethene was introduced in 2000.

  16. Ministry of Finance (2007, 2015) gives a detailed description of energy and environmental taxation in Norway in recent decades and of the international environmental agreements that Norway has signed.

  17. Electricity prices are firm-specific in the energy-intensive part of the manufacturing industries, because prices are regulated by long-term contracts (http://www.ssb.no/energi-og-industri/statistikker/elkraftpris). Firms outside the manufacturing industries purchase electricity at market prices.

  18. The input price of materials are proxied by Production Input Prices (Statistics Norway). This variable is at a detailed industry level. Firm variation is achieved through the dirty and clean energy prices.

  19. Using factor input prices, e.g. energy prices as proxies for environmental taxes is common in the literature, see, e.g., Jaffe and Stavins (1995). Fluctuations in relative energy prices caused by e.g. world market oil price changes contribute to sharper estimated coefficients of relative price changes—our measure of indirect regulations such as taxes.

  20. The following pollutants are related to energy use: \(CH_{4}\), CO, \(CO_{2}\), \(N_{2}O\), NMVOC, VOC, \(NO_{x}\), S, \(SO_{x}\). Moreover, the following pollutants are energy use related when they are emitted to air: AS, \(C_{2}F_{6}\), CD, \(CF_{4}\), \(CR-3\), \(CR-6\), \(CR-TOT\), CU, HG, PB, \(SF_{6}\), ZN. See Table A in the “Appendix” for a list of definitions of these pollutants. For an overview of the rest of the emission components included in the data we refer to Håndbok V712 2006, and Tables 50 and 52 (in the Annexes) in de Bruin et al. (2010), available at the homepage of CE Delft.

  21. Since we only include firms with emission permits we only study firms that are dirty. There are few dirty firms in less pollution intensive industries as services, retail trade, construction and transport.

  22. Even if all other variables are differentiated, \(V_{i,t-1}\) is a level variable measured relative to 0. A violation is in itself a change from steady state since the firm will at some point return to a complying state.

  23. By including the EU ETS dummy we separate the potential effect of the environmental taxes from the effects of the tradable EU ETS quotas, although they are probably very small, see also Sect. 3.2.2.

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Authors and Affiliations

  1. Statistics Norway, Oslo, Norway

    Brita Bye & Marit E. Klemetsen

  2. University of Oslo, Oslo, Norway

    Marit E. Klemetsen

Authors
  1. Brita Bye
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  2. Marit E. Klemetsen
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Correspondence to Brita Bye.

Additional information

We are grateful to Arvid Raknerud for many valuable suggestions and comments. Thanks also to Terje Skjerpen, Diana Iancu, Cathrine Hagem, Reyer Gerlagh, and participants at the 5th WCERE Congress in Istanbul and the 4th CREE workshop at Lysebu. Øyvind Hetland of the Norwegian Environment Agency has given us access to data and provided helpful information. While carrying out this research, the authors have been associated with CREE—Oslo Centre for Research on Environmentally friendly Energy. The CREE Centre acknowledges financial support from The Research Council of Norway, the University of Oslo, and user partners.

Appendix

Appendix

See Table A.

Table A Energy use related emissions
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Bye, B., Klemetsen, M.E. The Impacts of Alternative Policy Instruments on Environmental Performance: A Firm Level Study of Temporary and Persistent Effects. Environ Resource Econ 69, 317–341 (2018). https://doi.org/10.1007/s10640-016-0081-8

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