The impacts of deterrence, social norms and ...

Forest Policy and Economics 55 (2015) 10–20

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Forest Policy and Economics journal homepage: www.elsevier.com/locate/forpol

The impacts of deterrence, social norms and legitimacy on forest rule compliance in Ghana Sabaheta Ramcilovic-Suominen a,⁎, Graham Epstein b a b

School of Forest Sciences, Faculty of Science and Forestry, University of Eastern Finland, P.O. Box 111, 80101 Joensuu, Finland The Vincent and Elinor Ostrom Workshop in Political Theory and Policy Analysis, Indiana University, 513 N. Park Ave., Bloomington, IN 47408, USA

a r t i c l e

i n f o

Article history: Received 4 May 2014 Received in revised form 15 March 2015 Accepted 15 March 2015 Available online 11 April 2015 Keywords: Forest policy Regulatory compliance Ghana Motivations Norms Legitimacy

a b s t r a c t Compliance is one of the central, but often overlooked challenges that actors face as they seek to devise and implement environmental policies. Therefore this paper draws upon multiple models of rule compliance to assess the factors influencing compliance in the high forest zone of Ghana. Specifically, the paper considers whether compliance with formal laws that prohibit the felling of timber trees, farming in forest reserves and the use of fire to clear land is explained by perceptions of government enforcement, social norms and/or the perceived legitimacy of rules and government officials while controlling for a number of potentially intervening factors, and each other. The results indicate that compliance is affected by deterrence, social norms, and the perceived fairness of laws; but more importantly it demonstrates that the factors affecting compliance vary across the three studied rules. Whereas compliance with the tree-felling rule is driven by government enforcement; compliance with the fire and farming rules appears to be linked to social norms and the fairness of rules. Given that levels of compliance are considerably higher for the bushfire and farming rules; we conclude by suggesting greater attention on the normative aspects of the compliance decision, and legal reforms that might align legislation with the social norms and practices of local users. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Legal and regulatory compliance plays a central role in good governance, democratic stability and sustainable development. Zaelke et al. (2005:30), for instance suggest that “sustainable development depends upon good governance, good governance depends upon the rule of law, and the rule of law depends upon effective compliance”. Indeed formal laws, informal rules and social norms act as an important form of social capital that may guide groups towards socially efficient solutions where individual and collective interests diverge (Coleman, 1987; Ostrom, 1990; Rayner et al., 2010). However, the ability of those rules to generate efficient solutions depends on the extent to which they are able to produce high levels of compliance among affected parties. In fact a number of recent initiatives including the EU Forest Law Enforcement, Governance and Trade (FLEGT) Action Plan (EC, European Commission, 2003) highlight illegal harvesting as a key driver of deforestation; and place compliance at the centre of the policy agenda. Therefore a core question for scholars of social–ecological systems and policymakers, alike, is to better understand the factors affecting compliance with forest laws and the ways in which policies might be designed to encourage broad-scale compliance (Cashore, 2002; Bernstein, 2005; Hansen, 2011). ⁎ Corresponding author. Tel.: +358 505714605. E-mail address: sabaheta.ramcilovik-suominen@uef.fi (S. Ramcilovic-Suominen).

http://dx.doi.org/10.1016/j.forpol.2015.03.006 1389-9341/© 2015 Elsevier B.V. All rights reserved.

High levels of non-compliance and other illegal forest activities are ubiquitous in many developing tropical countries (SCA and WRI, 2004; Tacconi, 2007; Turner et al., 2007). In recognition of this problem, the European Commission coordinated discussions that culminated in the EU FLEGT Action Plan (EC FLEGT briefing notes, 2004–2007). The Action Plan aims to combat illegal logging by strengthening the enforcement of forestry laws in timber-producing countries, and prohibiting imports of illegal timber into the EU. Moreover, it seeks to strengthen forest governance and build capacity in partner countries with the long-term goal of enhancing the social and economic well-being of forest communities (EC, 2003, 2005). In September 2008, the first of these voluntary partnership agreements (VPAs) was finalised with Ghana (EC-Ghana, 2009). The performance of the VPA between Ghana and the EU will ultimately depend upon its ability to generate sufficient and appropriate incentives to encourage individuals to forego the short-term benefits of illegal harvests. Thus it is crucial to develop a better understanding of the factors affecting compliance in order to design and implement forest policies that are likely to resolve the problem of illegal forest activities. Contemporary compliance theory recognises three main classes of compliance motives; i) instrumental factors which include the expected benefits of illegal harvests and expected costs imposed by monitoring and sanctioning systems (i.e. deterrence), (ii) social norms, and (iii) the perceived legitimacy of rules, rulemaking processes, and the actors charged with designing and implementing those rules

S. Ramcilovic-Suominen, G. Epstein / Forest Policy and Economics 55 (2015) 10–20

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Fig. 1. Map of Ghana showing Districts included in this study and the forest cover. The map is based on Food and Agriculture Organisation of the United Nations (FAO) Global Cover Regional Africa Achieve.

(Ramcilovic-Suominen and Epstein, 2012). However, important gaps remain with respect to our understanding of which, if any, of these factors have a greater influence on individual rule compliance; and whether the factors affecting compliance vary across rules and regulatory contexts. Therefore this paper considers the factors affecting compliance with three separate forest rules in Ghana's high forest zone. The results broadly support each major component of contemporary compliance theory by showing that compliance tends to increase as perceptions of peer compliance, deterrence and the fairness of rules increase; but that the effects of compliance motives vary across the three studied rules. The remainder of the paper is structured as follows. First we begin by providing some background information about forest governance in Ghana and introduce the specific forest rules used in this analysis. In

Section 3 we discuss theoretical models of rule compliance and the analytical framework used in this study. Section four describes the data collection protocol and statistical methods used in this analysis; the results of which are presented in Section 5. Finally, Sections 6 and 7 conclude the paper by discussing the implications of the results for the development of compliance theory and the design of forest policies. 2. Forest governance in Ghana Over the last century, Ghana has lost nearly 80% of its original forests (Repetto, 1990); and recent studies suggest that illegal harvests are a leading cause of deforestation. Hansen and Treue (2008) estimated that 70% of all timber in Ghana is harvested illegally and that informal small-scale operators serving domestic markets are responsible for

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approximately three quarters of this total. Between 1996 and 2005, annual timber harvests have ranged between 3.3 and 3.7 million m3, compared to an annual allowable cut of 1.0 million m3 (Hansen and Treue, 2008). A majority of Ghana's natural forest resources are found in the high forest zone (HFZ), an area of approximately 8.5 million hectares which contains both formally protected forest reserves and off-reserve areas (Forestry Department Ghana, 1999; Boateng et al., 2009). Many of Ghana's forest reserves were established under colonial rule between 1920 and the late 1940s (Kotey et al., 1998). The off-reserves, on the other hand, include a mixture of farmland with naturally occurring timber trees, and patches of natural forest (Amanor, 1996; Boateng et al., 2009). Trees found in off-reserve forests and farmlands are important sources of timber for both “legal” timber companies and “illegal” chainsaw operators. Although technically illegal farmers tend to prefer to grant access to chainsaw operators as they derive a greater share of the benefits (Marfo, 2010). Chainsaw milling, however, became so widespread in the early 1980s that it was banned in 1998 to regulate the flow of timber (Act 547). Chainsaw milling has, however, thrived despite the ban as a result of inconsistent enforcement, and sustained demand for timber (Marfo, 2010). Since the introduction of the Concessions Act in 1962 (GoG (Government of Ghana), 1962), the rights to manage and harvest all naturally-occurring timber trees – regardless of location or tenure arrangement – are held by the central Government (Acheampong and Marfo, 2009; Amanor, 1999; Boateng et al., 2009). In fact the laws governing the rights to use forest and tree resources in Ghana are quite complex and depend upon a number of factors, including but not limited to land ownership. (Agyeman, 1993; Acheampong, 2003; Acheampong and Marfo, 2009). The rights to harvest trees that are planted by communities or individuals are held by the planter of trees. However, the right to plant trees is granted to landowners only. Although there is no customary or statutory law that prohibits tenants from planting trees, such actions are perceived as an attempt to acquire permanent ownership of the land and are strongly discouraged by landowners (Acheampong and Marfo, 2009). The rights to naturally occurring non-timber trees, on the other hand, depend on whether the trees are used for commercial or subsistence purposes. The rights to non-timber trees with commercial value (e.g. kola, oil palm, raphia palm, bamboo) are restricted and held by landowners; while the rights to trees of subsistence value (e.g. fruit trees) belong to the whole community (Agyeman, 1993).

2.1. The question of forest legality and the EU FLEGT VPA in Ghana The forest regulation reforms that were initiated in the early 1990s as part of the New Forest and Wildlife Policy (1994) gave rise to a number of policy changes. Collectively these policy changes created a dual governance system whereby commercial timber rights are allocated only to registered companies via competitive bidding processes; while communities can obtain timber utilisation contracts to harvest timber for non-commercial purposes. As the EU FLEGT action plan began to take shape, a number of factors ultimately contributed to Ghana being chosen for the initial VPA. First, at the time of negotiations approximately 60% of Ghana's timber exports were sent to EU countries (Beeko and Adelle, 2009). Second, and perhaps most importantly Ghana was seen as a partner with genuine interests in reducing illegal logging, but one which thus far had failed to appreciably meet its goals and could therefore benefit from the programme. While negotiations on the VPA began by focusing exclusively on bilateral trade it soon became clear that the programme would need to expand to include the domestic and other international markets to prevent leakage. As a result, the scope of the signed VPA was expanded to include all timber harvests, including those occurring on farms and off-reserve areas (EC-Ghana VPA, 2009).

2.2. The three studied forestry rules 2.2.1. The tree-felling rule The 1962 Concession Act (GoG (Government of Ghana), 1962) specifies that rights to harvest and manage all timber trees, including those on private land and farms, are held by the state (Act 647). Commercial use rights are allocated exclusively to incorporated companies or individuals via competitive bidding processes (L.I. 1721); while local communities and non-governmental organisations can apply for permits to fell trees for non-commercial use (L.I. 1649). The permission of landowners is also required to fell trees on non-public land. As a result of these policies most timber harvests on privately held farmland are considered illegal. The so-called ‘tree-felling rule’, thus, refers to the prohibition imposed on farmers to fell or grant access to fell timber trees on their farmland for small-scale commercial purposes; or for domestic purposes without a government issued permit. 2.2.2. The farming rule Farming in the forest reserves is considered illegal, c.f. the Forest Protection Decree 1974 (FPD, 1974), and the Forestry Protection (Amendment) Act, 2002 (FPAA, 2002). According to this Act, it is an offence to cultivate any farm in a forest reserve, without written consent of the competent forest authority. Written consent for farming in forestry reserves can be issued on the basis of: (i) admitted farms, and (ii) Modified Taungya System (MTS). Admitted farms are legally acknowledged farms in forest reserves. Nowadays such farms are exceptionally rare in Ghana. The MTS is a type of agroforestry, which allows temporary intercropping of food crops in the first years of forest plantation establishment (Agyeman, 2006; NFPDP (National Forest Plantation Development Program), 2007). The so called ‘farming rule’ in this research refers to prohibitions to farm in a forest reserve without a written consent of the competent authority (FPD, 1974). 2.2.3. The bushfire prevention rule Farmers use fires, for various activities, including farming (e.g. smallscale land clearance, and traditional slash and burn agriculture), hunting for bushmeat, and cultural practices. After the devastating wildfires in 1982/1983, Ghana adopted a number of legal and policy instruments concerning bushfire management (WMP, 2011). The current law regulating bushfires is the 1990 Control and Prevention Bushfire Act (CPBA, 1990). This law decentralised the regulation of bushfires to the district level. Thus, there is a fire sub-committee under each District Assembly, which enacts by-laws (set of rules and regulatory measures) to ensure prevention, control and monitoring of bushfires, at the district level. These bushfire by-laws generally include: prohibition of early cultivation and associated burning in the dry season, prohibition of using fire in forests or farmlands, for any purpose in the dry season, and obligation to make fire belts and attend to the fire, in agricultural practices. ‘Bushfire prevention rule’, as defined in this research, refers to legal requirements to follow these regulatory measures. 3. Theoretical and analytical framework of rule compliance Contemporary compliance theory has built upon economic models of rule compliance to suggest that compliance depends upon a number of social, economic and political factors; as well as the context in which compliance decisions are made (Ramcilovic-Suominen and Epstein, 2012). In general compliance theory recognises three major models of individual rule compliance. The first of which is known as the deterrence model. The deterrence model is based on rational choice theory and emphasises the role of self-interest and rational calculations of benefits and costs (Becker, 1968). According to this model, individuals elect to obey laws because they expect that costs imposed by monitoring and sanctioning systems would exceed the benefits of illegal activity (Ehrlich, 1973).


Sociologists and a growing number of social scientists contend, however, that a great deal of compliance can be explained by institutions and social norms. Institutional and social norm-oriented models of compliance (Posner, 1997; Cialdini and Trost, 1998; Elster, 2009) emphasise the extent to which human beings tend to conform to the expectations of appropriate behaviour within a group or culture; although they do not always agree as to why conformity tends to occur. For those that view “institutions as constraints” (Coleman, 1987); compliance or conformity is the result of peer pressure and an expectation of social sanctions if they fail to conform. In contrast, those that view “institutions as preferences” argue that individuals learn to value choices that conform to social expectations (Gintis, 2009). There is, however, a third approach, the “institutions as rationalities” school which argues that human beings switch between economic and social logics depending upon the context in which decisions are made (Vatn, 2005; March and Olsen, 2006). For instance, social norms might predominate in the context of repeated interpersonal exchange; while economic factors drive behaviour in corporate or business contexts. In a more specific example, Cardenas et al. (2000) used a field experiment to find that groups are more likely to cooperate when they choose rules than when a rule is imposed, even when the imposed rule is welfare enhancing. Finally, the third model of compliance emphasises the role of legitimacy (Tyler, 1990; Nielsen, 2003; Feld and Frey, 2007). Legitimacy refers to a complex set of factors surrounding the creation, content and implementation of rules and laws. In general the literature on legitimacy highlights issues surrounding the (i) general validity of government authorities or local leaders; (ii) the process by which rules are created, and (iii) the fairness and effectiveness of the resulting rules. A synthesis of the three main models of individual rule compliance was organised into an analytical framework for the study of forest law compliance in Ramcilovic-Suominen and Epstein (2012); and is used as the basis for the analysis in this paper. The framework distinguishes between factors perceived as individual motivations (i.e. instrumental factors, norms and legitimacy) and those perceived as external contextspecific factors, which represent the context in which individual compliance decisions are made. The block of individual motivations include three groups of factors. First, the instrumental factors highlight economic motivations such as the expected benefits of illegal harvests, expected costs via monitoring and sanctioning systems and, discount rates. Second, the norm related factors, include both social norms and personal norms (e.g. personal morals and values). Third, legitimacy related factors, include elements of procedural justice (e.g. participation, representation, transparency, accountability in decision making process) and outcome of the decisions (e.g. consistency and coherence of decisions and their distributional effects). Finally, the framework recognises that several external contextual factors including regulatory and legislative constraints, corruption, poverty, forest conflicts, forest culture, market signals and property rights might also influence compliance behaviour. The vast majority of contemporary empirical studies of rule compliance have taken place in the context of aquatic systems (Kuperan and Sutinen, 1998; Nielsen and Mathiesen, 2003; Viteri and Chávez, 2007; Eggert and Lokina, 2010; Madrigal-Ballestero et al., 2013; Hatcher et al. 2000); although there are some exceptions (Jenny et al., 2007). Nonetheless all of these studies adopt a broad conception of human motivation to suggest that compliance depends upon the distribution of benefits and costs, social norms and legitimacy; and then seek to test which of these factors account for compliance while controlling for the others and potentially intervening factors. In broad terms each of the compliance motives enjoys some level of support from the aforementioned studies. Social norms, which are typically measured by considering individual perceptions of the compliance of other resource users has a consistently, and with one exception (Jenny et al., 2007) significant positive effect on the likelihood of compliance. The multiple dimensions of legitimacy, on the other hand have varied levels of support. The perceived fairness of appropriation rules has a statistically

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significant impact on compliance in four of the six studies; while perceptions of relevant state actors are influential in only one of the five studies in which it was included. Finally, and perhaps surprisingly deterrence is only influential in three of the five studies in which it was included, which clearly supports the general hypothesis that compliance behaviour is determined by more than just the distribution of economic benefits and costs. 4. Methods: survey, variables and statistical methods 4.1. Survey Data for this study was collected using semi-structured interviews with a mixture of closed and open-ended responses. Interviews were conducted with the heads of farming households in 10 selected communities. The communities were randomly selected from a list of farming communities near the forest reserves (Fig 1) obtained from the forest district offices. An in-situ interview plan was made where the approximate shape and boundaries of each community as well as the locations of households for interviews were defined. The interview plan was followed as closely as possible; households that most closely coincided with the specified locations were approached and their heads were subsequently interviewed. In total, 226 heads of households were selected and interviewed. The sample includes 9.3% of the heads of households in the 10 selected communities. The fieldwork and data collection was performed by a fieldwork team consisting of the first author, one senior scientist and two fieldwork assistants from the Forest Research Institute of Ghana (FORIG) and a local guide. With a few exceptions interviews were conducted in Twi (the local language) and translated into English. The fieldwork (preliminary interviews, pre-tests and interviews) was conducted from April to July 2010. Each interview took between 1 and 1.5 h to complete. To promote accurate reporting, respondents were informed of the topic and aim of the research in advance and could choose to participate or decline their participation in the survey. They were assured that the research team has no relation to the forestry department. None of the approached interviewees declined to participate, allowing for a 100% response rate. The interviews include several sections that focus on forest values, compliance behaviour and perceptions concerning each of the three rules, as well as socioeconomic attributes and fundamental values; some of which are published elsewhere (Ramcilovic-Suominen, 2012; Ramcilovic-Suominen et al., 2012; Ramcilovic-Suominen and Epstein, 2012; Ramcilovic-Suominen and Hansen, 2012). This paper focuses on closed-ended single response questions to ask how different factors affect the decision to comply with forest rules. 4.2. Variables Tables 1 and 2 describe and summarise the variables included in this study. With the exception of political legitimacy and socioeconomic attributes, the remaining variables are related to specific forest rules. Forest law compliance – the dependent variable – records self-reported compliance of individual farmers with regard to each of the three studied forest rules: (i) bushfire, (ii) farming, and (iii) tree-felling. While the analytical framework presented in Ramcilovic-Suominen and Epstein (2012) includes a large number of factors that may influence the compliance decision, this analysis considers a smaller subset of these. First, practical constraints in terms of time and resources limited the range of data that could be collected from respondents. Second, the survey was designed for multiple method analysis and therefore included a variety of different types of questions including several open-ended questions that are more difficult to analyse with standard statistical techniques. The focal explanatory variables in this study include the following: (i) deterrence, (ii) peer behaviour, (iii) fairness of rules and (iv) political legitimacy. In addition, a number of socio-economic attributes, such as

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Table 1 Demographic and socio-economic information of respondents (Articles II and III) N = 226. Occupation (%)

Gender (%)

Age

Level of education (%)

Origin

Farmers/Carpenters/Hunters

Male/Female

With/Without formal education

Indigenous community/migrant

97/1/1

70/30

18–30/30–60/ N60 15/74/11

80/20

64/36

a

Average monthly incomea

Average household size

145 GHC (~100 USD)

7

Note that 70% of respondents had an income under the average.

gender, origin, age and income are used to control for variations across individuals. Whereas the analytical framework presented in Ramcilovic-Suominen and Epstein (2012) includes a number of additional social and political influences; these are not included in this analysis for important theoretical and methodological reasons. First, many of these factors affect compliance indirectly by changing individual perceptions about the distribution of benefits and costs, the strength and nature of social norms, and the legitimacy of rules and rulemakers. For instance, we would generally predict that levels of corruption and capacity to enforce rules are captured, at least in part, by individual perceptions of political legitimacy. Second, given that the sample consists of observations from a single region of Ghana they would exhibit limited, if any, variability and thus are unsuited to statistical analysis. Instead explorations of the effects of these factors would require a sample of individuals or communities with more diverse social and political contexts. The measures used in this analysis are described in Table 1 and further elaborated here. Deterrence is calculated as the product of an ordinal and dichotomous measure of the likelihood of detections and sanctions, respectively. The likelihood of detection explicitly refers to detection of rule violations by government forestry officials; and excludes informal systems of monitoring by members of the community. Peer behaviour, which is expected to correspond to social norms, is measured by performing a factor analysis on 2 indicators of community compliance. More specifically, survey respondents were asked whether they believe that community members comply with the rules and the

relative frequency of non-compliance by their 5 closest peers. The perceived fairness of rules is measured using an ordinal indicator ranging from very unfair to very fair. Finally, political legitimacy is measured using a factor analysis of three indicators concerning the behaviour of forest officials (i.e. level of satisfaction with the work, conduct and behaviour of forest authorities). 4.3. Statistical analysis The effects of the independent variables on the probability of compliance with each of the three forest rules are estimated with logistic regression models which are often used to study compliance behaviour in either binary or ordered form (Kuperan and Sutinen 1998; Hatcher et al., 2000; Eggert and Lokina, 2010). Logistic regressions are used to estimate models with dichotomous, ordered, or nominal dependent variables as they constrain predictions within the unit interval and do not impose a linearity assumption which allows the effects of independent variables to vary depending upon the value of that variable. In short, the logistic model overcomes the limitations of the linear probability model by estimating the log-odds of success (in this case comply with rules) as a function of a vector of independent variables (Long, 1997). As a consequence, however, the likelihood of compliance depends upon the values of all other independent variables in the model. Therefore in addition to a table of model coefficients, we use plots to facilitate analysis of the effects of independent variables at the mean of all other variables in the model.

Table 2 Variable description and summary statistics. Variable Rule compliance Self-reported compliance with forest rules 1 = Always; 0 = Never or sometimes

Deterrence Perceived probability of detection for each forest rule ∗ sanctions (1 = very unlikely, 2 = somewhat unlikely, 3 = somewhat likely; 4 = very likely) (1 = sanctions expected if detected ; 0 = no sanctions expected if detected) Peer behaviour Factor score of perceived levels of community and peer compliance with rules 1) Community-level compliance (1 = Very low; 4 = Very High) 2) Frequency of non-compliance by peers (1 = Often; 5 = Never) Fairness of rules Perceived fairness of operational rules (1 = Very unfair; 2 = Unfair, 3 = Fair; 4 = Very Fair)

Political legitimacy Factor score regarding perceptions of forest officials and their behaviour 1) Satisfaction with forest officials (1 = Not satisfied at all; 4 = very satisfied) 2) Respect forest officials (1 = don't deserve respect; 3 = deserve great respect) 3) Fairness of forest officials (1 = Never; 4 = Always) Socioeconomic profile Male (1 = Male, 0 = Female) Migrant (1 = Migrant, 0 = Indigenous) Age (1 = 18–30; 2 = 31–40; 3 = 41–50; 4 = 51–60; 5 = above 60) Income (natural logarithm of monthly income in Ghana Cedi)

Rule

Obs.

Mean

Std. Dev.

Min.

Bushfire Farming Tree felling

226 226 226

0.858 0.894 0.319

0.349 0.309 0.467

0 0 0

1 1 1


223 224 225

2.771 2.089 1.773

1.314 1.800 1.764

0 0 0

4 4 4


221 218 217

−0.007 0.002 −0.025

0.971 0.978 0.954


224 225 226

3.594 3.427 3.190

0.592 0.658 0.751

All

217

−0.006

0.972

−2.020

2.847

All All All All

226 226 225 218

0.699 0.642 2.778 4.480

0.460 0.481 1.193 1.015

0 0 1 1.609

1 1 5 6.908

−1.435 −1.623 −0.830 1 1 1

Max

1.206 1.009 2.623 4 4 4


As mentioned previously two of the independent variables, peer behaviour and political legitimacy are the result of a factor analysis of 2 and 3 indicators, respectively. Factor analysis is commonly used as a data reduction technique when scholars are interested in latent (i.e. unobserved and often unobservable) constructs. More specifically it allows scholars to overcome some of the limitations of single indicators by first determining: (i) whether two or more indicators load onto a common construct, and (ii) generating improved measurements of latent constructs of interest. This has the added advantage that it reduces the potential effects of multicollinearity if all factors were included in a regression model. The factor analyses were performed on the polychoric correlation matrix of the indicators reflecting their ordinal nature.

Table 4 Logistic regression results. Standard errors are clustered by community and reported in parentheses. Independent variables

Peer behaviour Fairness of rules Political legitimacy Deterrence Male

5. Results

Migrant

This section summarises the main findings of this study by first discussing (i) levels of compliance with each of the three forest rules, and then (ii) presenting the results of logistic regressions to evaluate the contributions of deterrence, social norms and legitimacy to the likelihood of compliance with each rule. 5.1. Farmers' compliance with studied forest rules in Ghana The summary statistics presented in Table 2 and further elaborated in Table 3 reveal fairly dramatic differences with respect to the level of compliance across the three studied rules. Compliance with both the farming and bushfire rule is fairly high, while over 68% of respondents reported violations of the tree-felling rule. Moreover, a substantial majority of respondents believed that other community members break the rule (83%) and approved of those violations (62%). With regard to the farming rule, a total of 10% of the respondents reported violations; 42% believed that other community members break the rule; and 31% approved of these violations. Finally, 13% of respondents reported that they would break the bushfire rule; 55% believed that their peers violate rules; and 21% approved of such violations. 5.2. Factors affecting compliance with forest rules The results of the logistic regressions for each of the forest rules are presented in Table 4 which reports the coefficients, as well as model statistics. Standard errors are clustered by community given that the sample consists of individuals from 10 separate communities. Model statistics such as McFadden's r-squared and the number of observations that are correctly predicted suggest that the vector of independent variables better explains compliance with the bushfire and farming rules than it does the tree-felling rule. The marginal effects of the independent variables are reported in Table 5. Marginal effects are calculated at the mean of continuous and ordinal variables, and for dichotomous variables they measure the discrete change in probability; while holding all other variables at their mean. For instance the marginal effect of the migrant variable is calculated by subtracting the predicted probability of compliance for an indigenous person (i.e. migrant = 0) from the predicted probability of compliance for a migrant (i.e. migrant = 1). 5.2.1. Deterrence and compliance: the role of monitoring and sanctioning Monitoring and sanctioning strategies are often cited in the commons literature as an important influence on the performance of

Table 3 Compliance with forestry rules. Percentage of respondents (N = 226). Situation

Tree felling rule (%)

Farming rule (%)

Bushfire rule (%)

a) Self-reported non-compliance b) Perceived non-compliance of peers c) Social approval for non-compliance

68 83 62

10 42 31

13 55 21

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Age Income Constant N McFadden's R2 Log-likelihood Wald χ2 p Correctly predicted (%) Mean VIF

Rule Bushfire

Farming

Tree felling

0.817*** −0.231 1.525*** (0.505) −0.029 (0.248) 0.167 (0.159) 0.257 (0.454) 0.538 (0.494) −0.145 (0.145) −0.313 (0.339) −2.295 (2.209) 202 0.225 −63.022 673.37 0.000 86.14 1.06

1.014*** (0.298) 0.809** (0.352) 0.151 (0.211) 0.067 (0.203) −2.319** (0.958) −0.336 (0.565) −0.104 (0.181) 0.340* (0.181) 0.794 (1.439) 201 0.249 −50.539 154.47 0.000 90.55 1.09

0.233 (0.221) 0.251 (0.268) −0.131 (0.215) 0.187** (0.085) −0.337 (0.320) −0.992*** (0.299) 0.347*** (0.116) −0.007 (0.182) −2.070 (1.582) 201 0.085 −112.943 51.42 0.000 70.15 1.11

***p b 0.01; **p b 0.05; *p b 0.1.

environmental governance systems (Chhatre and Agrawal, 2008; Coleman, 2009; Gibson et al., 2005; Ostrom and Nagendra, 2006). Moreover, the use of punishment to maintain social order possesses an equally strong theoretical basis in behavioural economics and the compliance literature (Becker, 1968; Henrich et al., 2006). Nonetheless, the results of our three statistical models suggest that deterrence has no impact on the farmer's compliance decision for two of the three studied rules. First of all, the combination of perceived probability of detection and a belief that one will be sanctioned if detected has no effect on the likelihood of compliance with either the bushfire or farming rule. Although, deterrence does have an impact on the likelihood of compliance with a tree-felling rule, the likelihood of compliance for an individual that believes that detection is very likely and expects to be sanctioned is only 37.5%1. This compares to approximately 22% for individuals that do not expect to be sanctioned for rule violation.

5.2.2. Social norms and compliance: the influence of social conformity The influence of social norms on the compliance decision is often highlighted in the literature on the commons, which draws particular attention to the role of trust and reciprocity (Ostrom, 1998; Ostrom et al., 1994). Perceptions concerning peer behaviour were used to measure social norms under the assumption that perceived levels of compliance corresponds to a latent social expectation (or norm) for that individual to comply. The results suggest that social norms have a positive effect on the likelihood of compliance with two out of three forest rules (farming and bushfire rules). This effect is plotted in Fig. 2 below, which reveals a general increase in the predicted probability of individual compliance as the perceived level of peer compliance increases from low to high values. It must be noted, however, that at even low levels of peer behaviour the predicted probability of compliance with farming and bushfire rules is very high, and that increased levels of trust only change the likelihood of compliance from very high to almost certain. 1 Note that this is calculated by holding deterrence at its maximum value, and all other independent variables at their mean.

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Table 5 Marginal effects. Independent variables

Peer behaviour Fairness of rules Political legitimacy Deterrence Male (d) Migrant (d) Age (d) Income

Rule Bushfire

Farming

Tree Felling

0.063*** 0.117*** −0.002 0.013 0.021 0.045 −0.011 −0.024

0.044*** 0.035** 0.007 0.003 −0.074*** −0.014 −0.004 0.015*

0.047 0.051 −0.027 0.038** −0.071 −0.211*** 0.071*** −0.001

(d) = discrete change; ***p b 0.01; **p b 0.05; *p b 0.1.

5.2.3. Perceived fairness of rules The logistic regression results also suggest that perceived fairness increases the likelihood of compliance with the farming and bushfire rules, but not the tree-felling rule. The effects of perceived fairness on the likelihood of compliance with these rules are plotted in Fig. 3. The effect is particularly noteworthy in the context of the bushfire rule where individuals that view the rule as fair as 30% are more likely to comply with the rule than an individual that views the regulation as unfair. 5.2.4. Political legitimacy and compliance The last major factor included in this study that is commonly proposed to directly influence the compliance decision is political legitimacy. Legitimacy is often highlighted by sociologists and political scientists that view compliance in terms of the perceived justice of rule makers and rulemaking processes (Tyler, 2006). In this case, the available measures refer only to the perceived legitimacy of forest officials and we are therefore unable to make inferences concerning the effects of procedural legitimacy. Nonetheless, the results suggest that the perceived legitimacy of forest officials has no effect on the likelihood of compliance with any of the three rules. More simply the behaviour and perceived attitudes of forest officials towards forest communities does little to alter the likelihood of individual compliance. 5.3. Socio-economic attributes and compliance Finally, the socio-economic attributes of forest users may also influence the likelihood of rule compliance (Eggert and Lokina, 2010) by affecting the set of incentives, opportunities and constraints that individuals face when choosing to comply or violate a forest rule. Once again, the results suggest that socioeconomic attributes have different

Fig. 2. Predicted probability of compliance with forest rule. Note x-axis has been standardised to vary from zero to one for each measure of peer compliance; all other values are held at their mean. Note that values for the tree felling are not significant.

Fig. 3. Predicted probability of compliance as a function of the perceived fairness of a rule. All other values are held at their mean.

effects across the three rules. First of all compliance with the bushfire rule is unaffected by any of the included socioeconomic attributes. In contrast, however, males are approximately seven percent less likely to comply with the farming rule, while those with higher monthly incomes are more likely to comply. Finally, the likelihood of compliance with the tree-felling rule is substantially lower among migrant community members, while it tends to increase with the age of the respondent.

6. Discussion The results of our analysis have several implications for compliance theory and the design of environmental policies. Before turning to these implications, however, it is important to note some of the limitations of this study. First of all the choice to sample a small subset of respondents from 10 separate communities allows us to explore factors affecting compliance across potentially heterogeneous social and ecological settings, but may overlook heterogeneities in the effects of compliance motives across communities. For instance it is possible that although deterrence does not have a statistically significant influence on the likelihood of compliance with the bushfire or farming rule in the sample of ten communities; that it might influence compliance in one or more of these communities. A second issue is related to measurement of compliance motives that might lead to erroneous results. This issue is perhaps the most salient in the context of deterrence which is commonly measured as the product of the likelihood of detection and the magnitude of expected sanctions (Becker, 1968). However, in this analysis we used a dichotomous indicator of whether any sanction was expected given the wide range of incommensurable monetary and non-monetary sanctions that were reported by respondents. Thus in the absence of variability in the magnitude of expected sanctions in this analysis it is possible that many of the expected sanctions are exceeded by the expected benefits of non-compliance and thus fail to generate the necessary economic incentives to comply. Third, and finally, reliance upon self-reported compliance might bias the results if participants fear potential repercussions of disclosing illegal behaviour, or simply under-report socially undesirable behaviour (Shadish et al., 2002). Although these cannot be ruled out entirely the use of self-reported compliance is consistent with other studies (Kuperan and Sutinen, 1998; Viteri and Chávez, 2007; Eggert and Lokina, 2010), and high levels of reported rule violations with the tree-felling rule suggest that participants were willing to share information concerning potentially undesirable behaviour. Therefore with these limitations in mind we now turn to the potential contributions of this study to compliance theory and the ways in which policies might be designed to increase prospects for compliance.


6.1. Implications for compliance theory Compliance theory developed rapidly throughout the 1990s as evidence mounted that compliance in particular and cooperation in general could not be explained by the distribution of short-term individual benefits and costs alone (Ostrom et al., 1994; Kuperan and Sutinen 1999). The results of this analysis clearly support this perspective by demonstrating that state enforcement has a limited impact on compliance with two of the three studied forest rules. Indeed, compliance with the bushfire and farming rules appears to be driven by a belief that the rules are fair and that others comply with rules; and is unaffected by monitoring and sanctioning systems. Whereas this appears to contradict a longstanding finding in the commons literature regarding the effects of monitoring and sanctioning (Chhatre and Agrawal, 2008; Ostrom and Nagendra, 2006); the lack of correspondence may be the result of important differences between local community-based monitoring (typical in the governance of commons), and external monitoring by government officials (which is relevant in the context of this study). Whereas external monitoring acts solely as an instrumental deterrent, community-based monitoring may also contribute to levels of trust and social capital in a community and may therefore activate normative motivations for compliance. In addition, it is important to note that the tree-felling rule is rather infamous in Ghana, as elaborated in Section 2. The absence of correlations between political legitimacy and compliance was expected and corresponds to earlier one-way relationships reported using the same data (Ramcilovic-Suominen, 2012; Ramcilovic-Suominen and Hansen, 2012); as well as other compliance studies (Hatcher et al., 2000; Eggert and Lokina, 2010). This does not necessarily imply that legitimacy itself is unimportant as legitimacy is invariably a multidimensional concept including attributes and perceptions of rulemaking processes (procedural legitimacy), rules (outcome legitimacy) and rulemakers (political legitimacy) (Tyler, 1990, 1990; Nielsen, 2003, 2003; Fragan and Tyler, 2004). This study focuses on perceptions of rules and the behaviour and conduct of political authority (Tyler, 1990, 2004); and omits process variables that have been influential in previous studies (Hatcher et al., 2000; Viteri and Chávez, 2007; Madrigal-Ballestero et al., 2013). Nonetheless given that this study emphasises formal government rules that apply throughout the country the influence of users from any particular community would be expected to be minimal. However, it would be interesting to compare the results of this study with a similar study of compliance with informal rules-in-use. Perhaps the most obvious, but nonetheless interesting result of this study is that the motivations that influence compliance differ across the three types of rules explored in this study. More specifically, compliance with the bushfire and farming rules were linked to social norms and perceived fairness of the rule, while compliance with the treefelling rule was linked to deterrence. This finding has three main implications for the study and development of compliance theory. First, if the motivations and factors that influence compliance differ across types of rules, then integration of a theory of compliance may be difficult unless accompanied by knowledge concerning the factors that drive these differences. Second, studies of compliance with regulatory systems (i.e. many rules) or rules in general may be highly sensitive to the specification of dependent and independent variables. For instance if we measured compliance in terms of compliance with all forest rules we would have observed low levels of compliance and likely overlooked the effects of social norms and fairness on compliance with the bushfire and farming rules. Finally the results seem to suggest that the study of rule compliance would likely benefit by focusing greater attention on the influence of normative aspects and motives (Crawford and Ostrom, 1995; Ryan and Deci, 2000) and motivation crowding theory (Frey and Jegen, 2001). Motivation crowding theory is a general theory of human motivation and ultimately behaviour that draws attention to the relationship

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between contexts and the set of normative and instrumental motivations that influence choices. It is commonly linked to the famous Titmuss2 hypothesis, but also shares several similarities with March and Olsen's (2006) alternative logics of consequences and appropriateness in political science, and self-determination theory in social psychology (Deci and Ryan, 2000). All of these theories highlight how different contexts generate distinct motives that are not necessarily commensurable or fungible with each other. Research in this area tends to focus on how the framing of situations leads to different and often economically irrational results, such as a decline in the willingness to accept nuclear waste facilities when financial compensation is offered (Frey and Oberholzer-Gee, 1997). Although crowding theory has received little explicit attention in the compliance literature, Gezelius (2004) describes how fishermen respond differently to non-compliance by food, small, and large-scale fishers. Non-compliance by food fishers is viewed with indifference or even supported as a legitimate right. Non-compliance by small-scale fishers is associated with small social sanctions, while large-scale fishers that break rules are sanctioned severely and condemned for threatening the common good. In essence the context within which the fishing activity affects the incentives and actions of fishermen as they respond to the breach of outwardly similar rules. Although a number of factors might be responsible for the differences in motives across rules; one possible explanation rests in the extent to which decisions by one individual potentially generate negative externalities affecting other individuals. Whereas farming in forest reserves can reduce the amount of land and/or forest products available to other individuals; and bushfires even when set on private land can spread to adjacent areas; the tree-felling rule when applied to trees on privately held land has no impact on the expected benefits and costs of other individuals. In other words individuals might be unwilling to comply with rules that apply to privately held land; even if they believe they are fair. However, it must be noted that there is insufficient evidence in this study to draw a strong conclusion regarding which if any factors are responsible for activating motives that drive compliance for each of the three forest rules. A second but related point is that with the general tendency to evaluate the effects of motivations and factors independently as we did in the Results section is that we risk overlooking important interactive effects (Ramcilovic and Epstein, 2012). For instance, although marginal effects and plots of the effects of social norms and perceived fairness of the rules take into account the full set of independent variables they are calculated at a single point for the remaining vector of independent variables. Fig. 4 reveals the potential problems with such an approach by illustrating the particularly large differences in the effects of social norms on compliance when rules are perceived to be fair and unfair, respectively. For example the predicted probability of compliance when the bushfire rule is perceived to be unfair and perceived peer compliance is high is only slightly higher than it is when the rule is perceived as fair and perceived compliance is low. In other words the predicted effects of changes in or more factors depend greatly upon the state of other factors. While interaction terms might be introduced into compliance models to assess their combined effects on the likelihood of compliance; they also tend to increase collinearity and reduce the power of statistical tests. An alternative approach which is growing in popularity is qualitative comparative analysis which is explicitly used to explore relationships between combinations of conditions and some outcome of interest, and has the added advantage in that it allows for the possibility of multiple causal pathways (Ragin, 1989; Rihoux, 2008).

2 Titmuss argued that blood donations would fall when monetary rewards were offered because they would undermine the pro-social values or motives that individuals gain (i.e. a warm glow) when giving blood voluntarily. A later test of this hypothesis observed this effect in women, but not in men (Mellstrom and Johannesson, 2008).

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Fig. 4. Predicted probability of compliance with forest rule when a rule is perceived to be fair and unfair. Note x-axis has been standardised to vary from zero to one for each measure of peer compliance. All other values are held at their mean.

6.2. Implications to forest policy: towards alternative rule compliance interventions The enforcement of forest laws and rules is commonly organised around a ‘traditional’ command-and-control approach. However, contemporary studies of forest law compliance, including this one, appear to lead in a different direction. This in turn has further implications for international forest policy instruments, such as the EU FLEGT and the Reduction of Emissions from Deforestation and Forest Degradation (REDD+). First, social norms and perceived fairness of rules matter. Therefore forest policies that encourage participation of all affected parties (most notably local users) and allow for a meaningful representation and consideration of their interests are advised. Although community participation typically involves substantial initial costs; such approaches often yield long-term dividends in the form of greater compliance, effectiveness and efficiency while also satisfying core democratic principles (Tyler, 1990; Nielsen, 2003; Viteri and Chávez, 2007). As a number of studies have shown, local communities can be motivated to conserve resources if laws provide appropriate and diverse incentives (Gregersen and Contreras, 2010; Jones et al, 2013). For instance, forest policies that strengthen the rights of farmers' to use, manage and/or own timber trees on their farms may generate incentives to reduce the rate of tree-felling in the studied communities. Various studies have identified a number of loopholes in the current forest policy, which vests ownership of timber trees with the state (GoG (Government of Ghana), 1962) and tends to favour large operators (Hansen, 2011; Hansen and Lund, 2011), limiting the flow of legal forest benefits to small-scale farmers. As a result, farmers perceive the regulation concerning the tenure and use of the trees on their farms to be discriminatory and unfair and consequently resist it by harvesting trees before they reach maturity to ensure that they capture the benefits (Amanor, 1996; Abane, 2009). Second, stricter enforcement of laws – through external monitoring and sanctions – does not necessarily result in better social and environmental outcomes. On the contrary, some of the most stringent forest policies and enforcement regimes are found in the countries with the highest rates of illegal forest activities (Cashore and McDermott, 2004; Tacconi, 2007). In this context, scholars emphasise the “barriers to legality” (Contreras-Hermosilla, 2003; Richards et al., 2003; Palo and Lehto, 2012), which paradoxically lead to increases in an activity after it is banned (e.g., the chainsaw ban in Ghana; Marfo et al., 2009), and intentional violation of rules that are perceived to be inconsistent and unfair (Peluso, 1992; Amanor, 1996; Abane, 2009). Our results are broadly in line with these studies, emphasising the role of fair rules on farmers' compliance behaviour. The one notable exception is the tree-felling

rule, where resource users that perceive the rule to be very fair are no more likely to comply than those that perceive the rule as very unfair. In other words the results suggest that attempts to encourage compliance by increasing the perceived fairness of the rule will have limited impact on behaviour; and will instead require investments in the monitoring and sanctioning mechanisms of the state. However, the ultimate environmental goals of the rule (i.e. the sustainability of timber harvests) might be better achieved by transferring greater authority to landowners to manage and harvest timber trees on their land to meet their subsistence and livelihood needs. More specifically, although compliance might be achieved by increasing monitoring and sanctioning for this rule, it may be more appropriate to change the rule to achieve a better balance of social and environmental goals. Although beyond the scope of this particular study, the factors that affect compliance may vary across user groups. For instance, it has been suggested that small, homogenous user groups, with a common history and shared culture, are more likely to be motivated by normative factors, in comparison to large user groups, such as international timber companies (Ostrom, 1990; Ramcilovic-Suominen et al., 2012: 51). The so-called “smart law enforcement interventions” or “alternative approaches to law compliance” (Gezelius, 2007; May, 2005; RamcilovicSuominen and Hansen, 2012), which apply different compliance measures – including discursive measures, information, cooperation, assistance, capacity building – according to variations in social and ecological contexts need to be explored and developed further. Lastly, in order to realise the full benefits of forest law enforcement initiatives, such as those designed for illegal logging in tropical countries, an expansive legal compliance system that applies a mixture of traditional (monitoring and sanctions) and alternative law compliance mechanisms (discourse, empowerment) is suggested. The emerging literature on rule compliance suggests that traditional law enforcement approaches can promote instrumental motivations for compliance, but are often costly to implement (Gezelius, 2002, 2004, 2007; May, 2005). The costs of implementation are especially high in situations where forests are distant from implementing agencies. In these cases, a more viable option might be to empower local forest users (Hirakuri, 2003; May, 2005). In theory, alternative approaches are associated with normative compliance motivations and an internal longterm duty to comply (Tyler, 1990; May, 2005). Farmers and local forest communities, when organised and motivated, can help monitor forest activities, report non-compliance by major law violators, and support forest officers in their efforts to promote pro-conservation behaviour and the rule of law. 7. Conclusions Farmers in the high forest zone of Ghana appear quite willing to comply with forest laws created and enforced by state actors. Indeed, the vast majority of farmers comply with laws that prohibit the setting of bushfires during the dry season and farming rules that prohibit the clearing of forest land for agriculture. Although a number of prior studies demonstrate that forest users are more likely to sustainably use natural resources when they are involved in the creation and enforcement of rules (Ostrom, 1990; Coleman, 2009; Chhatre and Agrawal, 2008; 2009); this study suggests that participation may not be absolutely necessary to ensure compliance in some contexts. Farmers that believe that the bushfire and farming rules are fair; and observe their peers complying with these rules are highly likely to comply with the rules themselves despite their lack of participation in its creation. In contrast, however, the tree-felling rule is violated by large majority of farmers, and only those that expect to be sanctioned choose to comply. Thus if the Ghanaian government wishes to encourage higher levels of compliance with the rule then it would appear that they could do so by increasing levels of enforcement. However, enforcement is a particularly costly activity and it is likely that the marginal costs of increasing enforcement would exceed the marginal social and ecological benefits it produces;


and could result in increased conflict between the state and resource users (Hara, 2005). Therefore, in the context of the tree-felling rule, a more prudent approach might be to consider the ultimate social and ecological goals of the state and resource users with regard to timber trees on privately held land; and develop alternative rules that balance these objectives before returning to the question of compliance. The EU with its VPA in place might be instrumental in this regard by applying external pressure for the State to consider the interests and participation of affected parties. The results also clearly support the general hypothesis that the likelihood of forest law compliance depends upon multiple motivations including levels of deterrence, social norms, and the extent to which rules are perceived to be fair and legitimate. This finding corresponds closely to previous research which demonstrates that compliance behaviour depends upon more than just the distribution of economic benefits and costs (Kuperan and Sutinen 1999; Viteri and Chávez, 2007; Eggert and Lokina, 2010). However, unlike prior studies which explored compliance with a single rule or regulatory system and exhibited variability in the specific types of factors that affect compliance; this study suggests that these differences might be explained by differences in the types of motivations that guide behaviour across different types of situations. For instance, while several statistical studies demonstrate a strong relationship between levels of enforcement and compliance (Sutinen et al., 1989; Viteri and Chávez, 2007); others studies find that compliance is better explained by social norms and perceptions about the content of rules (Kuperan and Sutinen 1999; Eggert and Lokina, 2010). In other words, although the second generation of compliance theory appears to have generally settled on the set of factors that potentially influence compliance behaviour; it would appear that the challenge for the next generation of compliance theory is to develop a better understanding of when each of those factors are likely to affect compliance. Acknowledgements Sabaheta Ramcilovic-Suominen thanks the Foundation for European Forest Research (FEFR) (14812) for financing support of this study and the European Forest Institute (EFI) for providing institutional support. Thanks are also to the University of Eastern Finland (project: Forest landscape restoration in Ghana: A multidisciplinary approach, grant number 14812), for supporting the fieldwork in Ghana. Katja Gunia from Arbonaut Oy Ltd. is heartily thanked for her assistance in producing the land-cover map of Ghana used in this paper. Finally, sincere thanks are to 226 farmers and their families, for dedicating their time, knowledge and experience to this study. References Abane, H., 2009. Livelihoods in a forest community in Southern Ghana: intervening policies and community resistance. J. Afr. Stud. Dev. 1 (2), 028–035. Acheampong, E., 2003. Sustainable Livelihoods of Forest Fringe Communities: Forests, Trees and Household Livelihood Strategies in Southern Ghana. PhD Thesis (unpublished), University of Hull, UK. Acheampong, E., Marfo, E., 2009. Forest and tree tenure, access to timber and their impact on chainsaw operations in Ghana. In: Marfo, E., Adam, A.K., Darko-Obiri, B. (Eds.), Ghana Country Case Study Report on Chainsaw Milling: Developing Alternative to Illegal Chainsaw Milling Through Multi-Stakeholder Dialogue in Ghana and Guyana. Final Report. CSIR-Forestry Research Institute of Ghana (FORIG) /Tropenbos International (TBI), pp. 75–107. Agyeman, V.K., 1993. Land, Tree and Forest Tenure Systems: Implications for Forestry Development in Ghana. A Report Submitted to the African Development Foundation, USA. Project grant number GHA. 420 (36p). Agyeman, V.K., 2006. Promoting smallholder plantations in Ghana. Plantations and Forest Livelihoods. AV31 Arborvitae 31p. 6 (September 2006). Amanor, K.S., 1996. Managing trees in the farming system. The Perspectives of Farmers. Forestry Department, Accra. Amanor, K.S., 1999. Global restructuring and land rights in Ghana. Forest food chains, timber and rural livelihoods. Research Report No. 108. Nordiska Afrikainstitutet, Uppsala (156 p). Becker, G.S., 1968. Crime and punishment: an economic approach. J. Polit. Econ. 76, 169–217.

19

Beeko, C., Adelle, C., 2009. The implementation of the EU's voluntary partnership agreement initiative to combat illegal logging: a Ghanaian perspective. Draft Paper Presented at: The External Dimension of Sustainable Development: International Conference on the External Aspects of the EU Sustainable Development Strategy (January 28, 2009, Brussels). Bernstein, S., 2005. Legitimacy in global environmental governance. J. Int. Law Int. Relat. 1, 139–166. Boateng, K., Okae, K., Hansen, C.P., 2009. Strengthening off-reserve timber resource management in Ghana. Tropenbos International — Ghana Workshop Proceedings 7 (Kumasi, Ghana). Cardenas, J.C., Stranlund, J., Willis, C., 2000. Local Environmental Control and Institutional Crowding-Out. World Development 28 (10), 1719-33. Cashore, B., 2002. Legitimacy and the privatization of environmental governance: how non-state market driven (NSMD) governance systems gain rule-making authority. Governance 15, 503–529. Cashore, B., McDermott, C., 2004. Global environmental forest policies: Canada as a constant case comparison of select forest practice regulations. International Forest Resources. International Forest resources, Victoria, BC. Chhatre, A., Agrawal, A., 2008. Forest commons and local enforcement. Natl. Acad. Sci. U. S. A. 105 (36), 13286–13291. Chhatre, Ashwini, Agrawal, Arun, 2009. Trade-offs and synergies between carbon storage and livelihood benefits from forest commons. Proc. Natl. Acad. Sci. 106 (42), 17667–17670. Cialdini, R.B., Trost, M.R., 1998. Social influence: social norms, conformity, and compliance. In: Gilbert, D., Fiske, S., Lindzey, G. (Eds.), The Handbook of Social Psychology, 4th edition . vol. 2. McGraw-Hill, New York, pp. 151–192. Coleman, J.S., 1987. Norms as Social Capital. In: Radnitzky, G., Bernholz, P. (Eds.), Economic Imperialism: The Economic Approach Applied Outside the Field of Economics. Paragon House Publishers, New York. Coleman, E.A., 2009. Institutional factors affecting biophysical outcomes in forest management. J. Policy Anal. Manag. 28 (1), 122–146. Contreras-Hermosilla, A., 2003. Barriers to legality in the forest sectors of Honduras and Nicaragua. Consultancy report (5 p). Crawford, S.E.S., Ostrom, E., 1995. A grammar of institutions. Am. Polit. Sci. Rev. 89 (3), 582–600. Deci, E.L., Ryan, R.M., 2000. The “what” and “why” of goal pursuits: human needs and the self-determination of behavior. Psychol. Inq. 11 (4), 227–268. EC (European Commission), 2003. Communication from the Commission to the Council and the European Parliament. Forest Law Enforcement, Governance and Trade (FLEGT) Proposal for an EU Action Plan, Brussels (21 May 2003. Com. 2003/251 final. 32 p). EC (European Commission), 2005. Council Regulation (EC) No 2173/2005, of 20 December 2005, on the establishment of a FLEGT licensing scheme for imports of timber into the European Community. Off. J. Eur. Union (6 p). EC FLEGT notes (European Commission FLEGT Notes), 2004–2007. FLEGT Briefing Notes (2004/5 series and 2007 series). EC, Brussels (http://ec.europa.eu/development/ policies/9interventionareas/environment/forest/flegt_briefing_notes_en.cfm. [Cited 18 Jun 2008]). Eggert, H., Lokina, R., 2010. Regulatory compliance in Lake Victoria fisheries. Environ. Dev. Econ. 15 (02), 197–217. Ehrlich, Isaac, 1973. Participation in illegitimate activities: a theoretical and empirical investigation. J. Polit. Econ. 81 (3), 521–565. Elster, J., 2009. Norms. In: Hedtröm, P., Bearman, P. (Eds.), Oxford Handbook of Analytical Sociology, Kindle ed. Oxford University Press (Chapter 9). Feld, L.P., Frey, B.S., 2007. Tax compliance as the result of a psychological tax contract: the role of incentives and responsive regulation. Law Policy 29, 102–120. Forestry Department Ghana, 1999. A Report Submitted to the African Development Foundation, USA. Project grant number GHA. 420. Fragan, J., Tyler, T.T., 2004. Policing, order maintenance, and legitimacy. Document No.: 207975. In: Mesko, Gorazd, Pagon, Milan, Dobovsek, Bojan (Eds.), This paper appears in Policing in Central and Eastern Europe: Dilemmas of Contemporary Criminal Justice. University of Maribor, Slovenia (and published by the Faculty of Criminal Justice). Frey, B.S., Jegen, R., 2001. Motivation crowding theory: a survey of empirical evidence. J. Econ. Surv. 15 (5), 589–611 (2001). Frey, B.S., Oberholzer-Gee, F., 1997. The cost of price incentives: an empirical analysis of motivation crowding-out. Am. Econ. Rev. 87 (4), 746–755. Gezelius, S.S., 2002. Do norms count? State regulation and compliance in a Norwegian fishing community. Acta Sociol. 45, 305–314. Gezelius, S.S., 2004. Food, money, and morals: compliance among natural resource harvesters. Hum. Ecol. 32, 615–634. Gezelius, S.S., 2007. Three paths from law enforcement to compliance: cases from the fisheries. Hum. Organ. 66, 414–425. Gibson, C.C., Williams, J.T., Ostrom, E., 2005. Local enforcement and better forests. World Dev. 33 (2), 273–284. Gintis, H., 2009. The Bounds of Reason. Princeton University Press, Princeton, NJ. Gregersen, H., Contreras, A., 2010. Rethinking forest regulations from simple rules to systems to promote better practices and compliance. The Rights and Resources Initiatives (41 p). Hansen, C.P., 2011. Forest law compliance and enforcement: the case of on-farm timber extraction in Ghana. J. Environ. Manag. 92, 575–586. Hansen, C.P., Lund, J.F., 2011. The political economy of timber taxation: the case of Ghana. For. Policy Econ. 13, 630–641. Hansen, C.P., Treue, T., 2008. Assessing illegal logging in Ghana. Int. For. Rev. 10, 573–590. Hara, M., 2005. Case for compliance studies to improve management of the Chambo on the south east arm of Lake Malawi. In: Banda, M., Jamu, D., Njaya, F., Makuliwa, M.,

20


Maluwa, A. (Eds.), The Chambo Restoration Strategic Plan. The WorldFish Center, Penang, Malaysia. Hatcher, A., Jaffry, S., Thébaud, O., Bennett, E., 2000. Normative and social influences affecting compliance with fishery regulations. Land Econ. 76 (3), 448–461. Henrich, J., McElreath, R., Barr, A., Ensminger, J., Barrett, C., Bolyanatz, A., Cardenas, J.C., Gurven, M., Gwako, E., Henrich, N., Lesorogol, C., Marlowe, F., Tracer, D., Ziker, J., 2006. Costly punishment across human societies. Science 312 (5781), 1767–1770. Hirakuri, S.R., 2003. Can law save the forest? Lessons from Finland and Brazil. CIFOR 2003 (131 p). Jenny, A., Hechavarria Fuentes, F., Mosler, H.J., 2007. Psychological factors determining individual compliance with rules for common pool resource management: the case of a Cuban community sharing a solar energy system. Hum. Ecol. 35 (2), 239–250. Jones, P.J.S., Qiu, W., De Santo, E.M., 2013. Governing marine protected areas: social–ecological resilience through institutional diversity. Mar. Policy 41, 5–13. Kotey, N.A., Francois, J., Owusu, J.G.K., Yeboah, R., Amanor, K.S., Antwi, L., 1998. Falling into place. Policy That Works for Forests and People. Series no. 4. International Institute for Environment and Development (IIED), London. Kuperan, K., Sutinen, J.G., 1998. Blue water crime: deterrence, legitimacy, and compliance in fisheries. Law Soc. Rev. 32 (2), 309–338. Kuperan, K., Sutinen, J.G., 1999. A Socio-Economic Theory of Regulatory Compliance. International Journal of Social Economics 26, 174-93. Long, J. Scott, 1997. Regression Models for Categorical and Limited Dependent Variables. Sage, Thousand Oaks, CA. Madrigal-Ballestero, R., Schlüter, A., Lopez, M.C., 2013. What makes them follow the rules? Empirical evidence from turtle egg harvesters in Costa Rica. Mar. Policy 37, 270–277. March, J.G., Olsen, J.P., 2006. The logic of appropriateness. In: Moran, M., Rein, M., Goodin, R.E. (Eds.), The Oxford Handbook of Public Policy, pp. 689–708 (2006). Marfo, E., 2010. Chainsaw Milling in Ghana Context, Drivers and Impacts. Tropenbos International, Wageningen, the Netherlands and CSIR Forestry Research Institute of Ghana, Kumasi, Ghana 978-90-5113-092-8. Marfo, E., Adam, K.A., Darko-Obiri, B., 2009. Ghana Country Case Study Report on Chainsaw Milling: Developing Alternative to Illegal Chainsaw Milling Through MultiStakeholder Dialogue in Ghana and Guyana. CSIR-Forestry Research Institute of Ghana and Tropenbos International, Wageningen Final report, 303 p. May, P.J., 2005. Regulation and compliance motivations: examining different approaches. Public Adm. Rev. 65, 31–44. Mellström, Carl, Johannesson, Magnus, 2008. "Crowding out in Blood Donations: Was Titmuss Right?". Journal of the European Economic Association 6 (4), 845-63. NFPDP (National Forest Plantation Development Program), 2007. National Forest Plantation Development Program. 2007 Annual Report (19 p). Nielsen, J.R., 2003. An analytical framework for studying: compliance and legitimacy in fisheries management. Mar. Policy 27, 425–432. Nielsen, J.R., Mathiesen, C., 2003. Important factors influencing rule compliance in fisheries lessons from Denmark. Mar. Policy 27 (5), 409–416. Ostrom, E., 1990. Governing the Commons. The Evolution of Institutions for Collective Action. Cambridge University Press, Cambridge. Ostrom, E., 1998. A behavioral approach to the rational choice theory of collective action: presidential address, American political science association, 1997. Am. Polit. Sci. Rev. 92 (1), 1–22. Ostrom, E., Nagendra, H., 2006. Insights on linking forests, trees, and people from the air, on the ground, and in the laboratory. Natl. Acad. Sci. U. S. A. 103 (51), 19224–19231. Ostrom, E., Gardner, R., Walker, J., 1994. Rules, Games and Common-Pool Resources. University of Michigan Press, Ann Arbor. Palo, M., Lehto, E., 2012. Private or Socialistic Forestry? Forest Transition in Finland vs. Deforestation in the Tropics. Springer (485 p). Peluso, N.L., 1992. Rich Forests, Poor People. Resource Control and Resistance in Java. University of California Press, Berkeley (336 p). Posner, R.A., 1997. Social norms and the law: an economic approach. The American Economic Review. Papers and Proceedings of the Hundred and Fourth Annual Meeting of the American Economic Association (May, 1997). vol. 87, No. 2, pp. 365–369. Ragin, Charles C., 1989. The Comparative Method: Moving Beyond Qualitative and Quantitative Strategies. University of California Press. Ramcilovic-Suominen, S., 2012. Forest Law Compliance in the High-Forest Zone of Ghana: an Analysis of Forest Farmers' Livelihoods, Their Forest Values, and the Factors Affecting Law Compliance Behaviour. (PhD Thesis). University of Eastern Finland, School of Forest Sciences 978-951-651-388-4. Ramcilovic-Suominen, S., Epstein, G. Towards an Analytical Framework for Forest Law Compliance, International Forestry Review Vol. 14(3), 2012, :326–336.

Ramcilovic-Suominen, S., Hansen, C., 2012. Why some forest rules are obeyed and others violated: instrumental and normative perspective of forest law compliance in Ghana. For. Policy Econ. 23, 46–54. Ramcilovic-Suominen, S., Matero, J., Shannon, M., 2012. Do forest values influence compliance with forestry legislation? The case of farmers in the fringes of forest RESERVES in Ghana. Small Scale For. http://dx.doi.org/10.1007/s11842-012-9209-z. Rayner, J., Buck, A., Katila, P., 2010. Embracing complexity: meeting the challenges of international forest governance. A Global Assessment Report Prepared by the Global Forest Expert Panel on the International Forest Regime. International Union of Forest Research Organizations (IUFRO) (172 p). Repetto, R., 1990. Deforestation in the tropics. Sci. Am. 262 (4), 36–42. Richards, M., Wells, A., Del Gatto, F., Contreras-Hermosilla, A., Pommier, D., 2003. Int. For. Rev. 5 (3), 282–292. Rihoux, B., 2008. Case-oriented configurational research: qualitative comparative analysis (QCA), fuzzy sets, and related techniques. In: Box-Steffensmeier, Janet M., Brady, Henry E., Collier, David (Eds.), The Oxford Handbook of Political Methodology. Oxford University Press, New York, pp. 722–736. Ryan, R.M., Deci, E.L., 2000. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am. Psychol. 55 (1), 68–78. SCA, WRI, 2004. Seneca Creek Associates and Wood Resources International. Illegal logging. American Forest & Paper Association (19 pp.). Shadish, W.R., Cook, T.D., Campbell, D.T., 2002. Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Wadsworth Cengage Learning. Sutinen, J.G., Gauvin, J.R., Gordon, D.V., 1989. An econometric study of regulatory enforcement and compliance in the commercial inshore lobster fishery of Massachusetts. In: Neher, Philip A., Arnason, Ragnar, Mollett, Nina (Eds.), Rights Based Fishing. Springer, Netherlands, pp. 415–431. Tacconi, L. (Ed.), 2007. Illegal Logging: Law Enforcement, Livelihoods and the Timber Trade. TIDD, 2010. Timber Industry Development Division Report on Export of Wood Products, Earthscan, London (January 2010. Available: http://www.fcghana. com/publications/industry_trade/export_reports.htm/year_2010/jan_2010.pdf Accessed 07/04/2010). Turner, J.A., Maplesden, F., Johnson, S., 2007. Measuring the impacts of illegal logging. ITTO Trop. For. Updat. 17, 19–22. Tyler, T., 1990. Why People Obey the Law. Yale University Press, New Haven. Tyler, T., 2004. Enhancing police legitimacy. Ann. Am. Acad. Pol. Soc. Sci. 593, 84–99. Tyler, T., 2006. Psychological perspectives of legitimacy and legitimation. Annu. Rev. Psychol. 57, 375–400 (2006). Vatn, A., 2005. Rationality, institutions and environmental policy. Ecol. Econ. 55 (2), 203–217. Viteri, C., Chávez, C., 2007. Legitimacy, local participation, and compliance in the Galápagos Marine Reserve. Ocean Coast. Manag. 50, 253–274. Zaelke, D., Stilwell, M., Young, O., 2005. Compliance, rule of law, & good governance. What reason demands: making law work for sustainable development. In: Zaelke, D., Kaniaru, D., Kruzikova, E. (Eds.), Making Law Work: Environmental Compliance and Sustainable Development. vol. 1. Cameron May Ltd, London (Chapter 1).

Referenced Acts and Legal Instruments CPBA, 1990. Control and Prevention of Bushfires Act, 1990. PNDCL, 229. Government Printer, Accra, Ghana. EC-Ghana (European Commission-Ghana), 2009. Voluntary Partnership Agreement between the European Community and Republic of Ghana on Forest Law Enforcement, Governance and Trade in Timber Products into the Community (Ratified by the parties in June 2009). FPAA, 2002. Forestry Protection Amendment Act, 2002. Act 624. Government Printer, Accra, Ghana. FPD, 1974. The Forest Protection Decree, 1974. NRCD 243. Government Printer, Accra, Ghana. GoG (Government of Ghana), 1962. Concessions Act. The Government Printing Department, Accra. The Forest and Wildlife Policy. The Timber Resource Management Act (Act 547). Timber Resource Management Amendment (Act 617). Timber Resources Management Regulations, 1998. (L.I. 1649). WMP, 2011. Wildfire Management Policy. Ministry of Lands and Forestry, Accra (March 25, 2015).