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Garbage In and Garbage Out? On Waste Havens in Switzerland

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Abstract

This study investigates whether the introduction of a unit-based garbage fee induces waste dumping in nearby communities which do not implement such a policy. To identify the existence of a “waste haven effect”, I hypothesize that the likelihood of “importing” or “exporting” waste depends on the distance to municipalities which have chosen the alternative policy option. Distances between municipalities are captured by routing data. I find some evidence for waste havens in a cross-section of Swiss municipalities. Exploiting variation in waste policy over time in a panel dataset for the canton of Ticino, I find that a decrease in distance is associated with an increase in the amount of waste collected by non-unit-pricing municipalities. The effect size is relatively small: An increase by one standard deviation in the impact factor applied to identify the waste haven effect increases the amount of collected waste per capita in non-unit-pricing municipalities by less than 3%.

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Notes

  1. See Bel and Gradus (2016) for examples of countries with unit pricing of household garbage.

  2. Aargauer Zeitung, 24.07.14. www.aargauerzeitung.ch, last accessed on 02.04.2015.

  3. The terms waste spillovers and waste haven effect describe the same behavior in this context and are used interchangeably throughout the paper.

  4. See, e.g., Oates (1999) for a discussion of fiscal federalism.

  5. There is a vast number of studies on the so-called “pollution haven effect”, which hypothesizes that industries relocate production due to changes in environmental regulations. See Copeland and Taylor (2004) and Copeland (2011) for reviews of the literature.

  6. Kinnaman and Fullerton (2000a) and Bel and Gradus (2016) provide reviews of this literature.

  7. No spillovers were detected for other types of waste.

  8. Garbage or waste here and throughout the paper is defined as the non-recycled (unsorted) leftovers of solid waste.

  9. I follow the notation of Kinnaman and Fullerton (2000b) when possible.

  10. Viscusi et al. (2011) separate between private values and external social norms. Here, both may induce such guilt costs.

  11. Dumping in public trashcans can be added to this group of options, at least for small amounts of garbage.

  12. Remember that \(g^i\) is the amount collected at the curbside. Accordingly, there is a difference between the amount of waste generated (\(g^i + x^i + b^i\)) and the amount of waste collected (\(g^i\)).

  13. Further details will be given in Sect. 3.

  14. It remains an empirical question how many of these bilateral relations are relevant for waste spillovers. The rationale of the unit pricing municipality suggests that waste should accumulate close to the border, as the exporting households try to keep their transport costs low.

  15. A similar hypothesis could be formulated regarding the expected fines for waste dumping. There is no available data on the height of fines, thus I leave such a hypothesis for future research.

  16. I thank the editor for this suggestion.

  17. Note that as I calculate \(\Delta \ln \ { Waste}\ p.c._{ij} = \ln { Waste}\ p.c._{i} - \ln { Waste}\ p.c._{j}\), the average difference is negative.

  18. Note that a regression discontinuity design, using road traveling time as the forcing variable, could only identify the joint effect of unit pricing and waste spillovers at the border.

  19. Even though Bel and Gradus (2016) found that accounting for endogeneity of unit prices does not significantly influence the elasticities estimated in the literature.

  20. See Table B1 in the “Appendix” for precise information on data sources. Data was unavailable for certain municipalities within some of the cantons. In the canton of Ticino, I drop the observations which report exactly the same amount of waste per capita as other nearby communities—as it indicates that figures were jointly reported to the office for waste and hazardous waste sites (Ufficio rifiuti e siti inquinati) which then split the data at the municipal level, keeping the amount of waste per capita constant.

  21. More precisely, only the canton of Nidwalden had municipalities without unit pricing in 2012 which are missing in the sample.

  22. I report estimates that include the canton of Vaud in Online Appendix B.2. The mentioned measurement errors make it likely that the regressions excluding Vaud are the more credible estimates.

  23. Unfortunately, most cantons are unable to provide information about the date when their communities switched to unit pricing, which consequently limits the possibilities for panel investigations.

  24. I cross-checked distances with Google maps routing data. Mapquest consistently estimates lower traveling times (i.e., approximately 5–10% lower) between municipalities; as this study is more interested in relative than absolute distances between communities, this does not qualitatively affect our results.

  25. As no data on waste per capita is available for municipalities of Nidwalden, they are not included in the sample for the following regression analysis. As the 11 municipalities of Nidwalden had not introduced unit pricing in 2012 and are thus potential waste havens, the distance to these municipalities was still taken into account when computing the distance measure for the unit-pricing municipalities in the sample.

  26. The left slope of Fig. 3a is not significant, while the right slope in Fig. 3a is significantly different from zero. The results of the univariate regressions are provided in Table B3.

  27. Due to data constraints, I cannot control for the education level, but variables reflecting political preferences are included.

  28. This indicator is retrieved from recycling-map.ch, a web page that collects information on recycling stations in Switzerland. On this website, when one enters the name of a municipality, a list of recycling stations appears, including which types of waste they accept. In a minority of cases, the response includes collection stations which are close-by, but not within the municipality’s boundaries (e.g., intercommunal collection centers are mentioned even if outside the area of the municipality). Thus, the resulting count variable can be interpreted as the number of bulky goods collection centers that a municipality has on its own ground or close-by.

  29. Descriptions and sources of all variables are summarized in Table B2 in the “Appendix”.

  30. I also applied specifications using a squared income term to test for an environmental Kuznets curve-type relationship as found in Ichinose et al. (2015). I find no evidence for a hump-shaped relationship between waste per capital and income. Results are available upon request.

  31. The coefficient for population density becomes insignificant in the last specification, most likely due to collinearity with the “center”-dummy in the community-type fixed effects.

  32. All regressions are run using specification (1) in Table 1 using OLS estimation, and standard errors are clustered on districts.

  33. Potentially, higher income municipalities also have higher unit prices, which would favor waste spillovers.

  34. I further tested interactions of commuter-town dummies with distance and of the share of social welfare recipients with distance. Both coefficients are insignificant.

  35. The most striking difference is that in the subsample of non-unit-pricing municipalities, the share of foreigners shows a significant positive correlation with waste per capita in two of four regressions.

  36. I use the dyadic-robust standard errors made available through Cameron and Miller’s (2014) Stata code “regdyad2”.

  37. Note that the effect here becomes stronger when looking at the 10 min interaction term then for the 5 min interaction term. The shaded areas in Fig. 1c provide an explanation for this pattern: In the case of a waste haven behavior, they are larger the further the distance away from the border.

  38. Note that these point estimates may suffer from the endogeneity problems mentioned in Sect. 3.1. However, Table 6 presents results regarding the non-recyclable waste reduction that are very similar to those of the quasi-natural experiment in the canton of Vaud examined by Carattini et al. (2015). This calms concerns about endogeneity and unobserved heterogeneity.

  39. The Stata command “cgmwildboot” was used to compute the bootstrapped standard errors. Results are available from the author upon request.

  40. No municipality switched back from unit- to non-unit-pricing in Switzerland yet.

  41. Theoretically, this may not be true for unit-pricing municipalities: They might affect the distance by excessive waste spillovers, forcing others to introduce unit pricing, thus the distance to non-unit-pricing municipalities would increase.

  42. Standard errors are clustered on municipalities. The results are robust to clustering on the “circle” level (in Ticino “circoli”), which is one administrative level below the districts (“distretti”).

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Authors and Affiliations

  1. Faculty of Business and Economics, University of Basel, Peter Merian-Weg 6, 4002, Basel, Switzerland

    Tobias Erhardt

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  1. Tobias Erhardt
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Correspondence to Tobias Erhardt.

Additional information

I am grateful to Giulia Felber, Frank Krysiak, Reto Odermatt, Christian Rutzer, Michaela Slotwinski, Alessandro Tavoni, and Rolf Weder for valuable comments and discussions. Moreover, I thank participants of the Economics Lunch Seminar at the University of Basel, the 50th Annual Conference of the Canadian Economics Association, the 5th Annual AERE Summer Conference, and the 22nd Annual Conference of the EAERE for their remarks.

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Supplementary material 1 (pdf 246 KB)

A Appendix Tables

A Appendix Tables

See Tables 8, 9 and 10.

Table 8 Mathematical symbols listed in order of first appearance
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Table 9 Summary statistics cross section
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Table 10 Summary statistics panel data Ticino
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Erhardt, T. Garbage In and Garbage Out? On Waste Havens in Switzerland. Environ Resource Econ 73, 251–282 (2019). https://doi.org/10.1007/s10640-018-0260-x

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