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International environmental outsourcing

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Abstract

In recent years there has been a dramatic increase in the number of firms shifting stages of their production processes overseas. In this paper we investigate whether firms outsource the dirtier stages of production to minimise domestic environmental regulation costs—a process broadly consistent with the pollution haven hypothesis. We develop a theoretical model of international environmental outsourcing that focuses on the roles played by firm size and productivity, transport costs and environmental regulations. We test the model’s predictions using a firm-level dataset for Japan and do find evidence of an ‘environmental outsourcing’ effect.

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Notes

  1. A related literature looks directly at the impact of environmental regulations on productivity (see for example Aiken et al. 2009; Greenstone et al. 2011). The PHH is also closely related to the concept of carbon leakage which has encouraged a policy debate on possibility of border trade adjustments to compensate for firms relocating to low environmental regulation countries.

  2. The international trade literature regularly refers to the concept of ‘offshoring’ (e.g. Grossman and Rossi-Hansberg 2008) and several recent papers have attempted to address whether the US is ‘offshoring’, or displacing, its pollution (Kahn 2003; Levinson 2010). It should be noted that offshoring captures all firm activity undertaken abroad. These activities include FDI, joint ventures and arms length trade with affiliates and non-affiliates and hence the offshoring of pollution refers to pollution emanating from all of these activities. International outsourcing however refers only to arms length trade between firms where parts of the production process are undertaken by unrelated firms abroad. Outsourcing is therefore a more precise concept than offshoring. The studies that do look at US offshoring also do so at the level of the industry rather than the firm and as a rule find no evidence that the US has been systematically offshoring pollution.

  3. Although firms may undertake domestic and/or international outsourcing, the focus of this paper is on international outsourcing given the fact that regulatory differences between Japan and many developing economies are likely to be much greater than any regulatory differences within Japan.

  4. Technology differences in production can affect domestic outsourcing similarly although country-level regulations are more likely to result in similar production techniques within a country. Likewise, distances are likely to be lower within a country rather than between countries.

  5. The recent proliferation of trade models based on heterogeneous firms was motivated in part by the empirical studies on firm size, productivity and export behaviour by Tybout and Westbrook (1995), Bernard and Jensen (1995, 1999), Bernard et al. (2003), Aw et al. (2000), Pavcnik (2002) and Eaton et al. (2004).

  6. The level of exports is given by: \( {\text{export}}\,{ = }\,\left( {\sum\nolimits_{s = 1}^{S} {\phi B_{m}^{s} } } \right)\theta_{m} p_{mj}^{1 - \sigma } = \left( {\sum\nolimits_{s = 1}^{S} {\phi B_{m}^{s} } } \right)\theta_{m} \gamma^{1 - \sigma } \left( {(a_{j} + D_{m} )w} \right)^{1 - \sigma } \).

  7. The government sets regulations at z per unit of output a priori. To satisfy z, firms pay abatement costs which when paid reduces z to zero.

  8. Without loss of generality we assume the wage in the foreign country is normalized to unity and intermediate goods are produced under perfect competition and constant return to scale in the foreign country.

  9. To close the model, free entry and exit condition is required as mentioned above. Expected profits in the presence of two types of firms equal entry cost. The free entry and exit condition is re-written as: \( F_{E} = n\int {\pi_{m}^{o} (a_{j} )d\varPhi (a_{j} ) + n\int {\pi_{m} (a_{j} )d\varPhi (a_{j} ).} } \)

  10. In our model \( (\tau_{w} w^{*} + a_{j} w)^{1 - \sigma } > (a_{j} w + D_{m} w)^{1 - \sigma } \) always holds as long as \( O_{m} > A_{m} \) and \( \pi^{o} - \pi = 0 \) holds for a certain a. If \( O_{m} < A_{m} \) then all firms outsource because \( \pi^{o} - \pi^{A} = 0 \). To keep our case interesting we assume that \( O_{m} > A_{m} \).

  11. In more detail: \( \frac{{\partial (\pi^{o} - \pi )}}{{\partial a_{j} }} = \frac{{\gamma^{1 - \sigma } \theta_{m} E}}{{\sigma P^{1 - \sigma } }}(1 - \sigma )w\left\{ {(a_{j} w + \tau_{m} w^{*} )^{ - \sigma } - (a_{j} w + D_{m} w)^{ - \sigma } } \right\} < 0 \) because \( (a_{j} + D_{m} )w > a_{j} w + \tau w^{*} \;{\text{and}}\;\sigma { > 1} \).

  12. Outsourcing is here defined as the contracting out of a part of the production process that was previously handled by the firm itself.

  13. Although our dataset does provide the level of outsourcing undertaken by each firm, our interest is in the decision whether or not to outsource and the factors that influence this decision. We have therefore converted the level of outsourcing into a simple dummy variable equal to 1 if a firm undertakes any outsourcing and 0 otherwise. In a sensitivity analysis we report results based on the level of outsourcing and they are consistent with the main reported results. Unfortunately, our dataset does not provide the country that each firm outsourced to but simply the total value of overseas outsourcing. Note also that our outsourcing variable does not to indicate which part of the production process is outsourced. However, Ito et al. (2007) provide a detailed study of Japanese firm-level outsourcing and show that 52.8 % of outsourcing is to China, 21.9 % to ASEAN countries, 11.58 % to other Asian countries and just 11.47 and 2.24 % to the US/Europe and the rest of the world respectively. From 2002 to 2007 around 72 % of the increase in outsourcing is due to an increase in outsourcing to China.

  14. Although some firm-level abatement cost data are available for Japan, the firms in the sample do not match those in our sample, nor do they provide sufficient industry coverage to provide industry-level observations.

  15. Almost identical rankings are found when we rank our industries in terms of other combinations of the seven questions.

  16. The Japanese industries with the least number of firms answering the environmental questions are also very similar to US and UK industries with the least pollution abatement costs per unit of value added and include industries such as Clothing and Publishing.

  17. We acknowledge that a firm’s transport costs will be a function of both the weight of the product being shipped and the distance that the product has to travel and are likely to relate to the firm’s final product rather than intermediate inputs. Nevertheless, if we assume that the weight of intermediate inputs is correlated with the weight of the final product, and if the final products of firms are shipped similar distances, then transport costs are likely to provide some indication of the potential cost to the firm of importing intermediate inputs.

  18. The first quartile contains the firms with the lowest sales. Replacing sales with the number of workers produces almost identical results.

  19. Table 6 in the appendix indicates, for example, that the mean of the OUTSOURCE dummy is 0.061 implying that 6.1 % of the firms in our sample undertake international outsourcing. Similarly, 26 % of firms answered ‘yes’ to the environmental question 1, 2 or 3, 43 % answered ‘yes’ to the questions 4, 5, 6 or 7 and 57 % answered ‘yes’ to at least one of the questions 1–7.

  20. In terms of calculations, 0.063 = 0.26 * (2.41 * 0.1) where 0.273 is the odds ratio (minus 1) on TRANS and 2.41 is the in sample mean value of TRANS.

  21. These variables are defined in Table 2. We also performed a battery of sensitivity and robustness checks with various combinations of controls which did nothing to alter the general pattern of results. Space prevents us from reporting these results here.

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Acknowledgments

Access to official micro-data was arranged by the Research Institute of Economy, Trade, and Industry (RIETI). We are grateful for the support of the Daiwa Anglo-Japanese Foundation grant number 7741/7948 and the Leverhulme Trust grant number F/00 094/BH. We thank Toshiyuki Matsuura for assistance with data preparation and Eric Strobl, Toby Kendall, Facundo Albornoz and participants at a RIETI meeting for helpful comments and suggestions.

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Authors and Affiliations

  1. Department of Economics, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK

    Matthew A. Cole & Robert J. R. Elliott

  2. Keio University, Tokyo, Japan

    Toshihiro Okubo

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  1. Matthew A. Cole
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  2. Robert J. R. Elliott
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Correspondence to Robert J. R. Elliott.

Appendix

Appendix

See Tables 5, 6, 7.

Table 5 Data definitions and sources
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Table 6 Summary statistics
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Table 7 Correlation matrix
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Cole, M.A., Elliott, R.J.R. & Okubo, T. International environmental outsourcing. Rev World Econ 150, 639–664 (2014). https://doi.org/10.1007/s10290-014-0193-6

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