Abstract
Our objective is to analyze the effectiveness, against the illegal disposal of waste, of a licensing system that has been introduced in a waste management policy. We theoretically find enforcement leverage in the licensing system, and then examine the theoretical result empirically. The results suggest that extending liability to disposers, which forms the basis of the enforcement leverage, deters illegal disposal more effectively than increasing penalties for illegal disposal. We also obtain evidence of transboundary movement of illegal disposal, and find how the court determines penalties for illegal disposal.
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Notes
The Resource Conservation and Recovery Act (RCRA) Permit Program in the United States prohibits treatment, storage, or disposal of hazardous waste by any person who has not received an RCRA permit. The European Union has adopted a number of Directives aimed at harmonizing waste disposal policies throughout Europe. The Waste Framework Directive requires member states of the EU to establish both a network of disposal facilities and competent authorities with responsibility for issuing waste management licenses.
This property is specific to the Japanese program. For example, RCRA does not allow facilities, whose licenses are suspended, to have their licenses returned if they refrain from illegal operation for a number of years. Although these differences among several programs require a slight revision of our theoretical results in the Appendix, they do not affect the equation we estimate in this study.
Licensing is also proposed as an optimal waste under asymmetric information. Shinkuma and Managi (2011a) integrate in their static model licensing, disposer tax, fines, and manifest into an optimal waste management policy.
Under CERCLA, the Environmental Protection Agency can require liable parties to conduct cleanups of a contaminated property. Section 107 of CERCLA defines a liable party as: (1) the current owner and operator; (2) any owner or operator at the time of disposal of any hazardous substances; (3) any person who arranged for the disposal or treatment of hazardous substances, or arranged for the transportation of hazardous substances for disposal or treatment; and (4) any person who accepts hazardous substances for transport to the property and selects the disposal site. In some cases, banks that hold mortgages on property as secured lenders are included among CERCLA’s liable parties.
In the RCRA Permit Program of the US, owners or operators of hazardous waste treatment, storage, or disposal facilities are required to apply for RCRA permits. Those who generate waste must not pass on their hazardous waste to unauthorized treatment, storage, or disposal facilities. In the EU, operators of industrial and waste installations covered by the Integrated Pollution Prevention and Control Directive are required to obtain an authorization (environmental permit) from relevant authorities in EU countries. There, too, those who generate waste are prohibited from contracting with unauthorized WMFs.
As stated in the Appendix, unlicensed WMFs have no incentive to comply with the standard and always dump waste because operating without a license is prohibited by law. So the probability of detection of operating without a license is assumed to be equal to that of illegal disposal.
If the amount of waste illegally dumped in a prefecture the year before decreased, patrols and other precautions in that area tend to become laxer, which then could make it easier to successfully cover up illegal dumping in the present year.
The Japanese government obliges all prefectures to present annual report on discharge and illegal disposal of industrial waste for each material.
We studied 132 recorded cases of violation (discussed on the next page) through an online search of Kikuzo II Visual, a news database retrieval service of The Asahi Shimbun. In these cases, the courts dealt with dumping activities whose detection took about 3 years (i.e., the summation of waste over year t, t − 1, t − 2 equals waste detected and reported in the news of year t.
When i = j, we assume 1/d ij = 0.1. We also tried using the values 0.01 and 0.2, and the results are robust when the value is not so changed.
We also examined the deterrence effect of penalties by using the maximum possible penalties. However, the explanatory power of deterrence effect using the expected actual ones was better and therefore we apply only using expected actual ones.
The probability of detection is obtained by multiplying the probability of specifying the criminal by that of finding the crime or illegal disposal. The former data is published in the Annual Report on Illegal Disposal of Industrial Waste. Although the latter is not available, Ishiwata (2002) estimates it is around 1%. In Japan, annually about 400 million tons of industrial waste is generated and about the half (200 million tons) is treated off site before the final disposal. However, because the capacity of those facilities for treatment of waste is around 150 million tons, 50 million tons of waste cannot be landfilled in final disposal sites. This overflowed 50 million tons of waste is either recycled or illegally dumped. Ishiwata (2002) estimates the waste to be recycled is 10 million tons at maximum. Then 40 million tons of waste is possibly dumped each year. Because about 0.4 million tons of waste is annually found to be illegally dumped, the probability of finding illegal disposal is estimated to be about 1%.
The results shown in Tables 7 8, 9 and 10 indicate that if the regulator raises μ2 f′ by $100 per ton, the rate of illegal disposal would decrease by from 52 to 207.30%. Because we need the effect of raising, the expected penalty for the violation of consignment obligation or μ f′ by $1, the estimated coefficient must be multiplied by μ. Noting that the average of μ is about 0.007, the marginal deterrence effect is estimated between 0.364 and 1.449%.
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Acknowledgments
We are grateful to Yoshifusa Kitabatake, Toshiaki Sasao, Tomohiro Tasaki, Koki Oikawa, Yoichi Furukawa, and Hiroyoshi Fujiwara for their many helpful comments. We would like to thank Masashi Yamamoto and Daisuke Ichinose in particular for providing us with their database. This research was supported by Grant-in-Aid for Scientific Research (B).
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Appendix: Derivation of (2): The waste management cost of a marginal WMF that is indifferent as to compliance or noncompliance (\( \widehat{\theta } \))
Appendix: Derivation of (2): The waste management cost of a marginal WMF that is indifferent as to compliance or noncompliance (\( \widehat{\theta } \))
Let us consider a competitive economy which allows the existence of improper treatment of waste by WMFs in the equilibrium. Then, in the equilibrium, disposers must be indifferent as to the choice of consigning waste to licensed WMFs or to unlicensed WMFs. If we represent by and the waste price per ton offered by a licensed and an unlicensed WMF, respectively, the following equation must be satisfied in the equilibrium.
Consequently, the waste management fee charged by an unlicensed WMF (p 0) is lower than that offered by a licensed WMF (p 1).
WMFs have two options: proper waste treatment, or illegal dumping. Intuitively, WMFs that are licensed and have a relatively lower value of θ will comply with the required standard for waste treatment. On the other hand, WMFs with a higher value of will violate the standard. Note that all WMFs want to be licensed because the fee for waste treatment is higher for a licensed WMF [see (A1)]. Therefore, in the stationary state, there are three types of WMFs: licensed WMFs that will comply with the standard (let us call them compliant licensed WMFs), licensed WMFs that will violate the standard or illegally dump the waste but will still keep their licenses (noncompliant licensed WMFs), and WMFs whose licenses are suspended (unlicensed WMFs). Note that unlicensed WMFs have no incentive to comply with the standard, because any operations of an unlicensed WMF are themselves illegal.
To obtain the steady-state equilibrium, we have to compare the current-value profits from proper waste treatment and illegal dumping with each other. Before calculating them, we need to look at the following list of notations.
- \( \pi_{1}^{p} \) :
-
The current value of the total amount of profit that a compliant licensed WMF can earn from the current period to an indefinite future period. The superscript p and the subscript 1 represent proper waste treatment and the licensed WMF, respectively.
- \( \pi_{0}^{i} \) :
-
The current value of the total amount of profit that an unlicensed WMF can earn from the current period to an indefinite future period. The superscript i and the subscript 0 represent illegal dumping and the unlicensed WMF, respectively.
- \( \pi_{1}^{i} \) :
-
The current value of the total amount of profit that a noncompliant licensed WMF can earn from the current period to an indefinite future period.
- β:
-
The discount factor.
First we derive the current value of profit for proper waste treatment (\( \pi_{1}^{p} \)). A compliant licensed WMF earns every period. Then the following equation must be satisfied:
We can easily calculate \( \pi_{1}^{p} \) as follows:
Next, the current value of profit for illegal dumping can be derived as follows. The profit of an unlicensed WMF, \( \pi_{0}^{i} \), must satisfy the following equation:
Note that the expected fine imposed for illegal dumping is denoted by μf. In addition, if an unlicensed WMF is not caught operating without a license during the current period, the suspended license is returned to the WMF at the beginning of the next period and the firm becomes a noncompliant licensed WMF in that same period (the probability is). Otherwise, the license of the WMF continues to be suspended during the next period. Therefore, the expected profit earned by an unlicensed WMF from the next period to an indefinite future period can be written as the bracket in the second term of (A4).
Similarly, \( \pi_{1}^{i} \) for (the current value of profit of a noncompliant licensed WMF), we can obtain the following equation:
Note that a noncompliant licensed WMF has to pay a fine (f) and loses its license in the next period if illegal dumping is detected (the probability is μ), but otherwise it can keep its license in the next period, as shown in the bracket of equation (A5).
By (A4) and (A5) we can calculate \( \pi_{0}^{i} \) and \( \pi_{1}^{i} \)
Improper WMFs include both noncompliant licensed WMFs and unlicensed WMFs. Denote by and \( 1 - \alpha \) the relative proportion of unlicensed WMFs and noncompliant licensed WMFs among all WMFs illegally dumping waste, respectively. In the steady state, must stay at a unique value. Note that unlicensed WMFs can apply for and obtain a license in the next period if they are not caught operating without a license during the current period. In the steady-state equilibrium, then, the proportion of unlicensed WMFs that will acquire licenses in the next period (\( (1 - \mu )\alpha \)) must be equal to the proportion of the noncompliant licensed WMFs that lose their licenses in the same period (\( \mu (1 - \alpha ) \)). We can, therefore, obtain the steady-state value of α.
The expected profit of a WMF that illegally dumps waste represented by \( E(\pi^{i} ) \) in the steady state can be calculated as:
As stated above, whether WMFs choose proper or illegal dumping depends on the level of θ In other words, only licensed WMFs with a lower value of comply with the standard for proper recycling. We can now derive the critical value of θ that is represented by \( \widehat{\theta } \). Since the marginal licensed WMF with must be indifferent as to compliance or noncompliance, the following equation must hold:
By substituting (A6), (A7), and (A8) into (A9) and solving (A10), we can derive the critical value of θ (or \( \widehat{\theta } \)). The result is represented by (2) in Sect. 3.2.
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Shinkuma, T., Managi, S. Effectiveness of policy against illegal disposal of waste. Environ Econ Policy Stud 14, 123–145 (2012). https://doi.org/10.1007/s10018-011-0024-0
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DOI: https://doi.org/10.1007/s10018-011-0024-0