ENHANCING COMPLIANCE WITH ENVIRONMENTAL LAWS IN
DEVELOPING COUNTRIES: CAN BETTER ENFORCEMENT STRATEGIES
HELP?
OSTROVSKAYA, ELENA1
LEENTVAAR, JAN2
1
Lecturer, UNESCO-IHE Institute for Water Education PO Box 3015, 2601 DA Delft,
the Netherlands, eostrovskaya@yahoo.com
2
Professor, UNESCO-IHE Institute for Water Education PO Box 3015, 2601 DA Delft,
the Netherlands, j.leentvaar@unesco-ihe.org
SUMMARY
Implementation of environmental policies proves to be challenging worldwide,
especially in developing countries. The competition between individual and social
interests produces confrontation. Thus it is important to analyze the motivations to
comply and the behavior of regulated communities in differing developing countries.
This paper discusses a novel approach to this analysis in relation to environmental data
management, “Table of 11”, which is a tool developed for the Netherlands’ Ministry of
Justice. This paper also summarizes findings of studies of the main reasons behind noncompliance of environmental regulations in developing countries. The studies show that
monitoring and enforcement significantly impact environmental behavior and
environmental quality in developing countries, as well as indicate that there is more than
one pathway to high compliance. The paper highlights important considerations for
mastering enforcement strategies in developing countries while taking into account
differing countries’ contexts. This paper did not address official corruption, which
requires deeper analysis and rectification before developing countries can achieve the
most possible environmental compliance.
1
INTRODUCTION
Though the deterioration of environmental quality is a major worldwide concern,
full compliance with environmental regulations is rarely observed. As Kremlis and Dusik
(2005) note, environmental protection is traditionally fighting “for the place in the sun”
with the economic policies (“growth and competitiveness versus environmental
conservation”). Evidence from developed countries indicates that compliance rates rarely
reach 100%. For example, Russel (1990) reported the following rates of compliance with
air pollution limits by industrial sources in USA: percentage of sources in violation –
65%; percentage of time the sources were in violation – 11%; excess emissions as a
percentage of standards – 10%. According to Heyes (2000), the United Kingdom
published compliance rates with many key water quality standards that were significantly
below 100%, sometimes as low as 50%. The true compliance rates were likely to be even
lower. The Netherlands government initiated a special study initiated that revealed that
only 67% of industries complied with Surface Water Pollution Act (Eindrapport, 2002).
As summarised in Mitchell (1996), Sparrow (2000), and INECE (2009) the main
factors affecting compliance include economic, political, technological, personal, and
1
social ones. However, the most common explanation for non-compliance is insufficient
monitoring and enforcement of law.
A large and growing theoretical literature indicates that functional enforcement is
necessary to ensure compliance (e.g., Ehrlich, 1972; Stigler, 1970; Heyes, 2000; Sparrow,
2000; Zaelke et al, 2005). This is because functional enforcement methods serve as a
“deterrence”, which is defined as the act or means of changing people’s behaviour to
avoid a sanction (Silberman, 2000). Enforcement deters detected violators from breaking
rules again, and it deters other potential violators by sending a message that they may
experience the same adverse consequences for non-compliance. Some theorists assume
that effective enforcement may not require frequent or strict regulatory action. For
example, Harrington’s game theoretic analysis (1988) demonstrated that compliance may
be high even when the frequency and severity of enforcement actions are quite low. The
empirical evidence for this inference, however, is mixed. Livernois and McKenna (1999)
support this hypothesis, while Nyborg and Telle (2006) do not. Huang (1996), Rousseau
and Proost (2005), and Shimchack and Ward (2005) find that inspections and sanctions
are associated with improved future compliance and environmental performance.
Recent empirical evidence also indicates that credible enforcement may increase
beyond-compliance behaviour. Shimshack and Ward (2008) show that many plants with
discharges typically below legally permitted levels reduce discharges further when
regulators issue fines, even when issued on other plants. Also, non-compliant plants often
respond to sanctions by reducing discharges beyond reductions required by law. Thus,
increased enforcement protects the environment beyond deterring violations. Because
perception is so important in creating deterrence, how a government implements
enforcement actions is just as important as their existence alone. They can have
significant effects far beyond bringing a single violator into compliance if they are well
placed and well publicized (Heyes, 2000; Cohen, 2005; Malloy, 2003).
2
CONTRIBUTION AND RESEARCH QUESTION
Although studies show that effective compliance monitoring produces desired
results, the behavioral motivations and pathways underlying effective monitoring and
enforcement are not well understood. Also, there is not enough empirical evidence on the
impacts of monitoring and enforcement in developing countries. This paper reports the
study that attempts to contribute to these two understudied areas.
This paper also discusses a novel approach to environmental data management and
its applicability to studies in developing countries. This framework, “Table of 11”, is
approved by the Netherlands’ Ministry of Justice and used in the practice of the country’s
environmental agencies, compiles a comprehensive set of environmental indicators from
detailed interviews and field observations. This paper is based on application of the
framework from “Table of 11” to review environmental compliance behavior and
regulated entities’ attitudes towards environmental performance, monitoring, and
enforcement five studied countries: Kenya, Rwanda, Nigeria, Tanzania, and China. The
study’s investigation provides early evidence on environmental performance in
developing countries. Further, the methodology permits an understanding of not just
environmental outcomes, but the underlying motivations for those outcomes as well.
2
3
METHOD
To analyze regulatory compliance with environmental laws this study uses five case
studies carried out in 2007-2009 in selected developing countries. The study programmes
were designed and guided by a rational choice framework, based on the Becker study
(1968), and recent achievements in exploring regulatory compliance motivations
discussed above in the introduction section. Therefore, the range of variables from
traditional deterrence measures: risk of detection and sanction, expected benefits from
violation, etc., to social and moral measures: perceiving the regulation and the enforcers’
authority as legitimate, following the regulation due to peer pressure from the fellow
users and from the community, etc., was covered in the studies. The respondents were
chosen randomly and included both enforcers and representatives of regulated
communities in order to obtain a realistic picture of the current situation and to avoid
one-sided judgment. The study used questionnaires based on “Table of 11” tests (2006),
and was guided by the Table’s selection of explanatory variables. The questionnaires
included close- and open-ended questions.
The checklist of the “Table of 11” is composed of 11 dimensions containing
variables that relate to spontaneous compliance and to enforcement (Table 1).
Table 1: “Table of 11” dimensions and underlying assumptions
“Table of 11” dimensions
Assumptions
1) Spontaneous compliance dimension group
Spontaneous compliance dimensions - factors that affect the incidence of voluntary compliance
that is, compliance that would occur in the absence of enforcement
T1. Knowledge and quality If legislation is written in clear and understandable language, a
of rules
regulated entity will likely comply with a regulation.
T2. Cost-benefit
If material and non-material advantages of compliance are
considerations (including
perceived by a regulated entity being higher than those of violation,
implications for image)
and material and non-material disadvantages of compliance are
perceived being less, then a regulated entity will likely comply
with a regulation
T3. Level of acceptance
If a regulated entity (generally) accepts policy, laws, and
regulations, to which it should comply, it will likely be in
compliance
T4. Respect for official If a regulated entity respects official authority to setup and enforce
and informal authorities
regulation, it will likely be in compliance.
But if innate willingness, habit or values of a regulated entity
competes with official authority and regulation, it will likely violate
the regulation
T5. Informal control (peer If there is a possibility that non-compliant behaviour of a regulated
pressure)
entity will be detected and disapproved by third parties (i.e. nongovernment authorities), and the possibility and severity of
sanctions that might be imposed by third parties (e.g. loss of
customers/contractors, loss of reputation) are high, a regulated
entity will likely be in compliance.
2) Enforcement dimension group
Control dimensions - the influence of enforcement on compliance
T6. Informal report risk
If there is a possibility that an offence may come to light other than
3
during an official investigation and may be officially reported, a
regulated entity will likely be in compliance.
T7. Risk of inspection
If there is a high likelihood of being subject to an administrative
(paper) or substantive (physical) audit/inspection by official
authorities, a regulated entity will likely be in compliance
T8. Risk of detection
If there is a high probability of an official detecting an offence
during an administrative audit or substantive investigation, a
regulated entity will likely be incompliance.
T9. Selectivity
If there is an increased chance of control and detection as a result of
risk analysis and targeting of firms, persons or areas, a regulated
entity will likely be in compliance.
Sanctions dimensions - the influence of sanctions on compliance
T10. Risk of sanction
T11. Sanction severity
If there is a high likelihood of a sanction being imposed if an
offence has been detected through inspections and criminal
investigation, a regulated entity will likely be in compliance
If a sanction and adverse effects associated with imposing sanctions
(including loss of respect and reputation) are adequate to cause
damage and timely imposed, a regulated entity will likely be in
compliance.
For understanding compliance and compliance motivations, the application of
“Table of 11” variables resulted in five sub-groupings of regulated entities (according to
the English version of 2006):
 Unconscious compliers: do not know the rules very well but unknowingly
comply with them; usually copy the behaviour of others.
 Unconscious non-compliers: break the rules because they do not know the rules
well.
 Spontaneous compliers: know the rules and would comply with them even if
theoretically the government lacked enforcement measures.
 Conscious violators: know they are breaking the rules and consciously accept
the risk of being caught and sanctioned; and
 Compliers deterred by enforcement: know the rules and would break them, but
choose to comply because they disfavor undergoing enforcement activities.
The questionnaires included a special set of questions enabling a researcher to make
the estimation (can be found at www.iT11.nl). However, this compliance estimate does
not provide accurate numbers because the calculations are based on interviewees’
perceptions about portions of those sub-groups. The estimate provides a general picture
of the compliance rate in a regulated community.
The critical review of the instrument can be found in Elffers et al (2003), and in a
number of Dutch sources (Koenders & Ruimschotel, 2002; Ruimschotel et al, 1996; Van
Reenen, et al, 1996; Wietzema Menkhorst et al, 2002). Elffers et al (2003) pointed out
that the “Table of 11” is a conceptual scheme that can be used for surveys, expert
interviews (as it was done in our case studies), round tables, and ex ante evaluation of
laws.
The studies involved face-to-face interviews and direct field observations. Usually,
self-reporting from the target group is used as a method for data collection in this kind of
4
research (Elffers et al, 2003; Eggert and Lokina, 2010), however this study was mainly
aimed at gathering the opinions of enforcers about the regulatees’ behavior. The
interviews with regulatees were used for crosscheck analysis, especially to get a more
realistic picture of enforcement practices. The study relied more on expert opinion than
on survey self-reporting. This research design tried to avoid bias and errors common
when people were asked to assess their own violating behavior (Elffers et al, 2003). The
study chose randomly regulated entities, while enforcers were selected among notable
enforcing authority figures. This approach has limitations; one of the most important is
the limited number of respondents. Another limitation is that the issue of corruption was
mainly left out of the scope of the study, though we received some complaints about it
from the interviewed regulatees. However, the study is advantageously framed to
demonstrate the non-compliance from an enforcers’ perspective and to gather opinions on
improving enforcement.
4
COMPLIANCE WITH ENVIRONMENTAL LAWS IN DEVELOPING
COUNTRIES: CASE STUDIES
This section describes the five case studies that used the “Table of 11”, which were
conducted within the MSc programs in Environmental science at UNESCO-IHE Institute
for Water Education, Delft, the Netherlands, in 2007-2009 (Table 2).
Table 2: Summary of the case studies
Country, area
The law in question
Kenya, Lake Victoria
Kenya Fisheries Act (1991)
prohibits the use of certain fishing
gears and methods and fishing in
certain areas of Lake Victoria
Rwanda, Kigali region
Nigeria, Ogun State
Tanzania, Arusha region
China, Inner Mongolia
The Rwanda Environmental
Organic Law (2005) in the part of
wetland use regulation and
control
The Law for Preservation and
Control of Forest, cap 39 (1992)
Plant Protection Act (1997) in the
part of regulation of pesticides
retailing
Water and Soil Conservation Law
(1991)
Number of respondents
- 24 fishers
- 15 enforcers from the central
government enforcing body
- 21 enforcers from Beach
Management Units
- 13 wetland users
- 13 enforcers (regional)
- 10 managers of logging
industries
- 10 enforcers (national and
regional)
- 16 managers of retailing
companies
- 15 enforcers (regional)
- 8 managers of mining
companies
- 8 enforcers
Specialists conducted case studies for developing countries, justifying the use of
“Table of 11” this context because it provides a general picture of compliance. “Table of
11” also assesses the effectiveness of the enforcement strategies with respect to a
country’s environmental legislation. Analysis software is user-friendly and manages large
amounts of quantitative and qualitative data. Further, the software presents results in a
more understandable and visible way that is especially important to communicate the
5
results to stakeholders and the public. “Table of 11” is proven help enforcing bodies
improve their reporting and accountability if used on a regular basis.
There are limitations of using “Table of 11”: its rankings were found to be quite
subjective and sometimes ambiguous. As a result, an analyst handling the data needs to
be well trained to interpret the data properly; otherwise one may draw incorrect
inferences. Interpreting the controversial rankings also requires a sophisticated
understanding of enforcement program operations and a skill for diagnosing problems.
In addition, the Table’s eleven dimensions all have the same weight, while it is clear that
some of them can dominate others. For instance, this study mirrored Eggert and Lokina
(2010) to indicate that economic reasons often prevail over moral or normative ones.
“Table of 11” application enables an analysis of the major compliance and
enforcement characteristics in various countries and comparison for experiential learning.
Understanding of underlying motivations of regulated entities helps environmental
agencies evaluate the effectiveness of their tools and strategies to achieve compliance.
Performance analysis enables agencies to better employ and allocate their resources,
invest in activities that achieve results, and modify or disinvest from those areas that are
not producing results. Overall, “Table of 11” can help environmental agencies increase
their efficiency, effectiveness by using their limited resources in a more productive way.
Table 3 illustrates the motivations to comply in the countries under study.
Table 3: Motivations for compliance
“Table of 11”
Kenya
dimensions
Knowledge of law
+
Clarity of law
+
Cost/benefit of
0
compliance
Cost/benefit of
violation
Implications for image
0
Policy acceptance
+
Respect for official
+
authority
Social control
Risk of reporting
0
Risk of physical
0
inspection
Risk of detection
0
Selectivity of
inspection
Risk of sanction
+
Severity of sanction
-
Rwanda
Nigeria
Tanzania
China
+
0
0
0
0
+
+
-
+
-
-
-
0
0
0
0
+
-
+
0
0
0
+
0
+
+
0
-
0
+
-
+
0
0
0
0
0
-
+
-
+
0
-
“- ” – a dimension has score showing that it has negative effect on compliance
“0” – no influence or dimension slightly encourages compliance
“+” – a dimension has score showing that it encourages compliance
Although data is based on a limited number of interviewees, the study still offers
valuable information. For example, in spite of differences between the countries, they
6
experience similar problems in implementation of environmental laws: the level of
compliance is rather low (Figure 1), and the governmental agencies are facing serious
enforcement problems.
China
Tanzania
unconsciously compliant
consciously compliant
Nigeria
deterred by enforcement
consciously violating
unconsciously violating
Rwanda
Kenya
0%
50%
100%
Figure 1: The level of compliance with the environmental laws in countries under study
Compliance levels can vary dramatically from case to case, whether it is a countryto-country comparison or an internal comparison. In all five countries studied,
environmental legislation is relatively new and changing, which makes it difficult to
enforce. The emphasis on economic improvement or expansion often causes
environmental protection to fall to the bottom of the governmental priority list (OECD,
2000). Economic reasons often prevail over moral or normative reasons when the
regulatees decide whether to comply or violate a rule. Eggert and Lokina (2010) pointed
out that in Tanzanian Lake Victoria fisheries, Tanzanian fishers were poor and could not
afford moral and legitimacy concerns to the same extent as the fishers in industrialized
countries. Poverty’s influence yielded higher non-compliance rates compared to those of
fisheries in industrialized countries.
Compliance depends mostly on the governmental willingness to enforce a specific
law. Enforcing agencies in developing countries are not mature enough and lack the
ability and capacity to perform their activities properly. There is a lack of formalized
procedures to plan and set priorities that can help enforcers to use their limited resources
more productively. Some countries, like Rwanda, are just beginning to develop data
systems. However, in the absence of organized efforts to collect and report data, even
basic analysis of the situation is difficult to accomplish.
Another important lesson is that enforcers should design their strategies to reflect
that different groups of regulatees have different motivations to comply (see Table 3).
Resource users consist of 1) big business, and 2) small businesses, individuals, and each
group can demonstrate a variety of behavior and attitudes toward compliance with
7
environmental regulations. Our country case studies can also be divided into two groups
according to major characteristics and behavior of regulatees: 1) countries with many
large businesses (China, and Tanzania) and 2) countries with many individuals and smallscale businesses (Kenya, Nigeria, and Rwanda).
In general, authorities’ decisions have more influence on big business, which is
more sensitive to the public opinion. Big business is willing to adopt environmental
management systems (e.g., ISO 14000) and to comply with international standards in
order to compete on foreign markets (OECD, 2000; Yasamis, 2007; Ostrovskaya et al,
2009).). However, a majority of natural resource users in the developing countries, like
Rwanda, Nigeria, Kenya, are small businesses and therefore, enforcement strategies
should address the limitations of the small-scale sector while highlighting the importance
of reducing environmental degradation that result from their activities. Dasgupta (2000),
for instance, also indicates the limited coping abilities and lower environmental
awareness of small industries in India, and demonstrates that small business is more
reluctant to change, as compared to big industries. Dasgupta highlights sanction-based
strategy employed in order to force small industries to change technology and/or install
pollution abatement equipment and evaluated it as counterproductive and anti-poor.
Civil society can play an important role in creating effective social control over
industries and resource users. Experience of developed countries (Sparrow, 2000; Heyes,
2000; INECE, 2009) shows that nongovernmental groups (NGOs, neighbouring
businesses, individuals, professional associations etc.) can undertake a range of various
actions against violators and contribute to bringing them into compliance. They can
detect and report offences, negotiate with violators, comment on government
enforcement actions, and where the law allows, can take legal action against a violator for
non-compliance or against the government for not enforcing the requirements.
However, our case studies show that in the developing countries social control is
weak due to the current low level of public awareness and concern for the damage to
human health and local communities’ well-being caused by environmental
noncompliance (e.g. in China, Kenya and Tanzania). Institutions of civil society may be
weak in general (e.g. in Rwanda and Nigeria). Where social control and institutions are
weak, the only kind of their contribution to ensuring compliance, which was identified in
the cases, is reporting violations to government authorities when the latter provide
necessary facilities for that (e.g., hot-lines etc.).
Finally, authorities of the developing countries often encounter difficulties in the
practical application of legislation. Obligations imposed on regulatees are often
unrealistic or overambitious (e.g., in cases of China, Rwanda). Greenspan-Bell (2003)
also pointed out, that industrialized countries prescribed overambitious policies to
developing countries, however, the success of those policies were determined by local
traditions, culture, institutions, and infrastructure. Therefore, local context should be
taken into account when the good practices are transferred to developing countries.
Greenspan-Bell offered a sound suggestion that developing countries could consider a
tiered or timelined approach, that accounts for their capabilities and institutions by
selecting compliance-assisting tools after first asking what is achievable and easy to
monitor.
8
5
CONCLUSION
This paper has outlined a number of issues that affect regulatory compliance with
environmental laws in developing countries. The case studies were designed within the
‘‘rational choice’’ model and guided by the ‘‘Table of 11’’, which is an inventory of
relevant variables. We are not pioneers in using this framework in the context of a
developing country [see, for example, Eggert and Lokina (2010)], but believe our
research can contribute to the empirical evidence on its applicability to studying
regulatory compliance in developing countries. Our experience also indicates that the
‘‘Table of 11’’ scheme (for sorting out different influences within a rational choice
framework) turns out to be useful both for future research and for use by enforcing
bodies. For enforcers, better understanding of underlying motivations that shape
behavior of a regulated community enables them to master their strategies, to more
efficiently allocate their resources, to invest in activities that achieve results, and to
modify or disinvest from areas that are not producing results. This better understanding
consequently helps authorities to productively use their limited resources.
The findings obtained from this analysis clearly show the need for deeper analysis
or further investigation to understand the drivers and constraints that shape the behavior
of regulated entities in developing countries. This study did not address the issue of
official corruption. We are convinced that in many countries corruption compromises the
position of the enforcers and severely affects the credibility of enforcement. Corruption
requires deeper analysis and rectification before developing countries can achieve the
most possible environmental compliance.
6
ACKNOWLEDGEMENT
We appreciate the support by the Netherlands’ Inspectie Verkeer en Waterstaat and
UNESCO-IHE Institute for Water Education for conducting the research. All students of
UNESCO-IHE MSc programs who participated in case studies are gratefully
acknowledged.
7
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