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Climate policy, environmental performance, and profits

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Abstract

In this study we investigate how firm level environmental performance (EP) affects firm level economic performance measured as profit efficiency (PE) in a stochastic profit frontier setting. Analyzing firms in Swedish manufacturing 1990–2004, results show that EP induced by environmental policy is not a determinant of PE, while voluntary or market driven EP seem to have a significant and positive effect on firm PE in most sectors. The evidence generally supports the idea that good EP is also good for business, as long as EP is not brought on by policy measures, in this case a CO2 tax. Thus, the results provide no general support for the Porter hypothesis.

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Notes

  1. Lundgren and Marklund (2010) explicitly address the Porter hypothesis (Porter, 1991; Porter and van der Linde 1995). By dynamic Porter effect they refer to efficiency gains induced by current and past regulatory pressure. In another related study, Brännlund and Lundgren (2010) also use data from Swedish industry to assess the effect of the carbon tax on profits via technological progress and find that the tax induces technological regress in all sectors of manufacturing. The main difference in this study is that we look at policy channeled through EP and the effect on efficiency, not technological progress.

  2. A similar, but still quite different approach to ours, is adopted by Dam et al. (2009), who look at impact on cost and profit efficiency for a range of corporate social responsibility factors (KLD ethical rankings), where environmental issues are included.

  3. Our methodology is similar to the approach in Hamamoto (2006) and Yang et al. (2012).

  4. This argument is in line with the Porter hypothesis. Environmental policy brings with it information that makes firms aware about inefficiencies in their operational activities.

  5. In the productivity literature there are a few recent studies where EP is defined and calculated using actual data on emissions; e.g., Färe et al. (2004), Färe et al. (2006), and Färe et al. (2010). However, EP is not linked explicitly to profitability as we do here.

  6. A review of empirical studies on corporate social responsibility (CSR) and its impact on financial performance is provided in Orlitzky and Swanson (2008). See also Lundgren (2011) for a compact review of the literature and a general theory of the socially responsible firm and the potential motivations for voluntary responsible behavior.

  7. Stock prices, firm value, return on assets, Tobin’s q, etc.

  8. See discussion in chapter by P. Portney in Hay et al. (2005).

  9. Note that even policy induced EP is voluntary in a sense. A tax is not forcing but gives economic incentives and signals to a firm to change its behavior. What we mean here is that a fraction of a firm’s EP is triggered by policy, while if we consider total variation in EP, also market driven or voluntary variation is accounted for.

  10. The PE approach adopted is based on Kumbhakar and Lovell (2000) and Kumbhakar (2001). The stochastic frontier estimating approach is based on Battese and Coelli (1995) and Coelli (1996).

  11. In the empirical application, there is a potential problem that the tax rate is not strictly exogenous since the firm can adopt its production plans or fuel use to the tax scheme and exemption rules and thus alter (to some degree) the effective tax rate to a desired level. However, since the tax actually paid by firms rarely exceeds 0.5 % of total sales, we do not believe this to be enough incentive for the firms to allocate resources to “tax planning”. This is also confirmed by industry and governmental officials we have spoken to. Therefore, we assume the effective tax rate to be exogenous to the firm.

  12. For a more detailed presentation and discussion, see Brännlund et al. (2014).

  13. See also, e.g., Färe et al. (2004, 2010).

  14. To model the opportunity cost of reducing the by-product, good outputs are assumed strongly disposable and good outputs and bad outputs together weakly disposable. Furthermore, it is assumed that good and bad outputs are null-joint, i.e., good outputs cannot be produced without producing bad outputs (see, e.g., Färe and Grosskopf 2003).

  15. See the result section for a summary figure of calculated EP at industry sector level.

  16. In their applications R&D was the dependent variable and domestic environmental regulation was the policy variable.

  17. We chose not to specify a formal theoretical model based on optimization for EP. Given the environmental index in Eq. (1) it would, in theory, be possible to construct something looking like a “demand” function for EP. Since carbon emissions are a direct consequence of fossil fuel use, one could combine a demand equation for fossil energy with an output supply equation at time t + 1 and t, given a certain production technology, to achieve an estimable equation. However, exploring this possibility generated quite complex equations that are non-linear in parameters and variables, and the estimation proved to be non-trivial. Therefore, we propose a more straightforward “reduced” form equation to estimate.

  18. More details about what governs EP and why are provided in Brännlund et al. (2014).

  19. The size dummies are based on firms being divided into sector specific size quartiles based on number of employees.

  20. However, since EP captures changes between two consecutive periods, the trend is not expected to be strong over time, perhaps even non-existing.

  21. See Orlitzky et al. (2011) for a discussion on strategic or profit maximizing green behavior.

  22. The general outline of the modeling approach here follows Lundgren and Marklund (2010). However, EP is used as the main explanatory variable for efficiency, and not the CO2 tax.

  23. However, in the “efficient” price vector (p,w), it is homogenous of degree 1.

  24. As motivated in Sect. 3, it is appropriate to apply a short-run framework when estimating profit functions, modeling at least one input as quasi-fixed. Then, the most natural choice is the capital stock. Furthermore, as we aim at assessing the effects of CO2 taxation on energy efficiency use in production, we also model labor as a quasi-fix factor. It may seem controversial to regard the number of employees as exogenously given in the short run. However, this is not that far from the truth concerning the circumstances in Sweden. By the Swedish Employment Protection act (Lagen om AnställningsSkydd, LAS 11§) the term of notice is 1–6 months depending on time of employment. Furthermore, as a complement to LAS, nearly all industrial firms have collective agreement which is an agreement between employers’ and employees’ organizations. Not unusual, the collective agreement is additionally to the benefit of the employees. Hence, the term of notice can in certain cases exceed 6 months in practice. In this respect, both capital and labor (measured as number of employees) are sluggish compared to energy input.

  25. The exact specification of the log likelihood equation in a profit function setting is available from the authors upon request. However, it is very similar to the primal production version of the log likelihood specification in Battese and Coelli (1993, 1995), but with prices instead of quantities as explanatory variables.

  26. See e.g. Waddock and Graves (1997) for a discussion and investigation of the causal relationship between the “good actions” of a firm and its financial performance.

  27. SNI is the acronym for Svensk Näringsgrenindelning 2002, which is also known as the Swedish Standard Industrial Classification 2002.

  28. For more detailed results on the EP calculations, year-to-year and cumulative for different sectors and aggregations, see Brännlund et al. (2014).

  29. Energy intensive sectors are: Mining, Food, Pulp and paper, Chemical, Stone and mineral, and Iron and steel (SNI codes in Table 1).

  30. The reader is referred to Brännlund et al. (2014) for full disclosure of estimation results and panel data estimation procedure.

  31. Complete estimation results of the frontier and inefficiency equation for each sector can be obtained from the authors upon request.

  32. The stochastic frontier approach is pertinent, i.e., all estimations produce statistically significant inefficiency scores. That is, both sigma and gamma are statistically significant for separate sector estimations.

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Acknowledgments

The authors gratefully acknowledge financial support from the Swedish Energy Agency (STEM), and the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (FORMAS). Participants at the Agricultural & Resource Economics seminar at UC Berkeley (December, 2012), the Asian Pacific Productivity Conference (Bangkok, July, 2012), the EAERE meeting 2013 (Toulouse, June/July), and Dr. Lammertjan Dam (Groningen) are thanked for insightful comments and suggestions. The usual disclaimer applies.

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  1. Centre for Environmental and Resource Economics (CERE), SLU/Umeå University, Umeå, Sweden

    Tommy Lundgren & Per-Olov Marklund

  2. Centre for Regional Science (CERUM), Umeå University, Umeå, Sweden

    Per-Olov Marklund

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  1. Tommy Lundgren
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Correspondence to Tommy Lundgren.

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Lundgren, T., Marklund, PO. Climate policy, environmental performance, and profits. J Prod Anal 44, 225–235 (2015). https://doi.org/10.1007/s11123-014-0396-9

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