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Environmental recidivism in Sweden: distributional shape and effects of sanctions on duration of compliance
Environmental recidivism in Sweden: distributional shape and effects of sanctions on duration of compliance
Gebrenegus Ghilagaber 0
0 Department of Statistics, Stockholm University , 106 91 Stockholm , Sweden
The study examines the association between the size of previous environmental sanction charges and subsequent compliance towards environmental regulations. Data used for the study come from about 9000 Swedish firms fined sometime between January 2002 and December 2012. Probabilities of compliance across various levels of sanctions are estimated using life-table methods and tested for equality using standard nonparametric methods. Association between size of sanction charges and subsequent behaviour is modelled by proportional hazard model for the rate of recidivism as well as by a family of flexible parametric accelerated failure-time models for the duration of compliance. The results show that duration of compliance may be described by a log-normal distribution. Further, it is demonstrated that sanctions charges do have significant detering effects on the risk of recidivism though the strength of the detering effect depends on whether or not we account for other possible correlates of recidivism. Possible explanations of the results and their policy implications are discussed; limitations of the current study highlighted; and potential extensions for future studies outlined.
Environmental regulations; Environmental sanctions charges; Time to re-offens; Modelling duration data; Recidivism; Sweden
1 Introduction
The overall aim of this paper is to measure the effect of environmental sanction charges on
subsequent behavior with regard to violation to environmental regulations. Effect, in turn,
is defined as a change that has occurred as a result of a specific measure taken—that
otherwise would not have occurred or occurred at a latter time. It is then clear that it is not
& Gebrenegus Ghilagaber
an easy task to measure effect as there are many variables which may influence
environmental behavior of firms and individuals and the state of the environment, irrespective
of enforcement actions. Further, substantial time may elapse between the application of
enforcement measures and changes made evident in the environment.
National and international environmental agencies use a wide range of indicators to
assess environmental conditions in general and the efficiency of enforcement measures in
particular. One such measure suggested has been the extent of recidivism—the act of
repeating violation to environmental regulations after a firm has been fined (penalized) for
that behavior. Rates of recidivism and the duration in compliance have been suggested as
output measures (International Network for Environmental Compliance and Enforcement
2008). Potential flaws in using recidivism ratios as measures of regulatory efficiency is
outlined in a report by U.S. Environmental Protection Agency—Office of Enforcement and
Compliance Assurance (2008). The main concern is that it is not possible to generalize
observed recidivism rates among facilities which were inspected to those which were not
inspected because some entities will be missed committing acts which, if they were caught
to do so, would constitute recidivism. Because of this drawback, it is suggested to use a
measure of chronic noncompliance as an alternative to recidivism rates. A potentially
useful formulation of chronic recidivism suggested in the literature is the average or
median length of time facilities/firms spend in compliance/noncompliance.
However, little is known about the empirics of environmental recidivism. In particular,
to the best of our knowledge, there has not been any study proposing appropriate statistical
methods to analyze data on length of compliance (time to recidivism) and model its
association with background characteristics of facilities.
This paper attempts to fill this gap in the literature by presenting a number of statistical
procedures of varying degree of complexity. The procedures are then illustrated using data
on about 9000 Swedish firms which were fined sometime between January 2002 and
December 2012. The goal of the study is to examine the effect of the size of sanction on the
length of compliance.
In Sect. 2, we describe the data in more details. Section 3 presents a number of
appropriate statistical methods and illustrates them empirically. These methods include
Kaplan–Meier and Life Table methods for estimating survival functions; nonparametric
Log-Rank and Breslow (Generalized Wilcoxon) tests for comparing the survival functions,
Cox proportional hazard model for the rate of recidivism as well as a family of flexible
parametric accelerated failure-time models for the duration of compliance. The last section
ties up the contents of the paper in the form of concluding remarks, outline of limitations of
the study, and potential extensions for further study.
2 The data set
Since 1999, the Swedish Environmenta (...truncated)