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Trade-based adoption of voluntary environmental programs in the developing world: Racing to the top or stuck in the mud?

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Abstract

Scholars have consistently found that firms in developing countries adopt voluntary environmental programs (VEPs) in high numbers when their major trade partners are home to many VEP-certified firms. This reflects the following dynamic: Importers based in countries with many VEP-certified facilities demand similarly sustainable production processes from trade partners, and so exporting firms in partner countries adopt VEPs to signal their sustainable practices. Studies have identified characteristics of developing countries that make local exporting firms more likely to adopt VEPs as a signal; however, there has been little analysis as to the country-level characteristics that make importers more (or less) likely to demand VEPs from suppliers abroad, beyond having many VEP-certified firms themselves. This study considers this matter, theorizing that VEP diffusion only accompanies exporting to countries with high levels of income and education, as well as a high number of VEP-certified firms. Panel data analysis provides support for the theory, showing that developing countries only experience trade-based diffusion of ISO 14001 (a widely adopted VEP) through their exports to countries with high income and/or education levels. In contrast, exporting to countries that lack these characteristics creates no such diffusion, even where importing countries’ VEP certification levels are high. Instead, such trade produces a “stuck in the mud” effect, as developing countries’ certification levels stagnate even as those of their import partners rise.

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Notes

  1. See Vogel (2008) for a thorough review of this scholarship. See also Andrews (1998) for discussion of firm-level environmental self-regulations.

  2. There are a wide variety of VEPs and they vary in design and effect; see Darnall and Carmin (2005).

  3. See Arimura et al. (2016) for literature review and discussion as to the effects of ISO 14001 adoption on environmental performance.

  4. Evidence for a race to the bottom in other areas of social development is more mixed. For example, Kaufman and Segura-Ubiergo (2001) find that economic openness is accompanied by decreasing rates of social spending in developing countries, whereas Rodrik (1998) finds that countries that are more open to trade have higher levels of government spending. Studies of labor rights have also produced mixed results: Davies and Vadlamannati (2013) find that competition for foreign investment has driven down labor standards in developing countries, whereas Greenhill et al. (2009) find that good labor laws diffuse through trade.

  5. The term “California effect” was introduced by Vogel (1995), who observed that US states followed California’s lead in adopting stringent emission standards.

  6. Work by Perkins and Neumayer (2012) and Saikawa (2013) finds that this pattern is also evident in the diffusion of emissions standards policy.

  7. It should be noted that there is some reason to think that VEP adoption produces economic benefits for firms (Rivera 2002), although evidence is decidedly mixed (Blackman and Rivera 2011).

  8. It should be noted that firms in the USA were slower than those in Japan and the European Union to adopt ISO 14001 or to demand adoption from suppliers abroad (Delmas 2000).

  9. The literature also identifies several variables contributing to green consumption that are not readily analyzable at the cross-national level, such as emotions, habits, and personal norms See Joshi and Rahman (2015) and Peattie (2010) for meta-analyses of individual and situational factors that contribute to green purchasing decisions.

  10. The sample countries are listed in Table 6 in Appendix.

  11. GDP is adjusted for purchasing power parity (PPP). Data for this variable was provided by Berliner and Prakash (2013), who also use this measure in their analysis.

  12. This alternative variable is analyzed below in a robustness test.

  13. Variants of this approach were used by Gamso (2017a, b).

  14. The Atlas methodology is explained in detail here: https://datahelpdesk.worldbank.org/knowledgebase/articles/378832-the-world-bank-atlas-method-detailed-methodology.

  15. Data for education is drawn from Barro and Lee (2013). These data are recorded in five year intervals (1950, 1955, 1960, 1965, and so on). I matched this with my dataset such that country-years after each observation were informed by that observation; thus, if a country had an education rate of 9 percent in 2000 and 11 percent in 2005, then it was grouped in the lower education categorization from 2000 through 2004, and in the high education categorization from 2005 through 2009.

  16. Schooling may be more rigorous in some countries than in others, such that an individual who has completed tertiary school in, for example, Egypt, may be less well trained in some regards than an individual who did not complete tertiary school in the USA. Nevertheless, I treat education levels consistently across countries, following the classifications from Barro and Lee (2013).

  17. See Table 7 in Appendix for a list of country-years in each category.

  18. Literature on other VEPs suggests that characteristics of CEOs may also be a contributing factor (Rivera and De Leon 2005), although to my knowledge this has not been attended to with regards to ISO 14001.

  19. Descriptive statistics for all of the variables analyzed in this study are featured in Table 8 in Appendix. A correlation matrix of independent variables is provided in Table 9 in Appendix (STATA omits variables automatically if severe collinearity is detected; no such collinearity is evident in the models analyzed for this paper).

  20. Data for this variable was provided by Berliner and Prakash (2013).

  21. The alternative approach for count data, a Poisson model, underestimates standard errors in cases of overdispersion, whereas a negative binomial model estimates a dispersion parameter and, therefore, allows analysis of overdispersed counts.

  22. In effect, (X − mean(X))3 can serve as an instrument for X.

  23. There are no results to display, but I include the code in my replication materials (available on request).

  24. Recent firm-level work does indicate that FDI produces effects consistent with a race to the bottom under some circumstances and effects consistent with a race to the top in other circumstances (Bu and Wagner 2016).

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  1. Thunderbird School of Global Management, Arizona State University, 1 Global Place, Glendale, AZ, 85306, USA

    Jonas Gamso

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Appendix

Appendix

See Tables 6, 7, 8, and 9.

Table 6 Countries in sample
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Table 7 Country categorizations for independent variables
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Table 8 Descriptive statistics
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Table 9 Correlation matrix
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Gamso, J. Trade-based adoption of voluntary environmental programs in the developing world: Racing to the top or stuck in the mud?. Policy Sci 51, 515–543 (2018). https://doi.org/10.1007/s11077-018-9319-3

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