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ANALYSIS

Factors affecting women's participation in forestry in Turkey

Erdoğan Atmişa,⁎, I·smet Daşdemira, Wietze Liseb, Ömür Yıldıranc

aUniversity of Zonguldak Karaelmas, Bartın Faculty of Forestry, Bartın, TurkeybEnergy Markets and International Environmental Policy Group, ECN Policy Studies, Energy Research Center of the Netherlands (ECN),Amsterdam/The NetherlandscBalıkesir Forest Enterprise, Balıkesir, Turkey

A R T I C L E I N F O

⁎ Corresponding author. Bartın Faculty of Fore2277421.

E-mail addresses: atmis@foresteconomiclise@ech.nl (W. Lise).

0921-8009/$ - see front matter © 2006 Elsevidoi:10.1016/j.ecolecon.2006.02.016

A B S T R A C T

Article history:Received 31 October 2005Received in revised form29 December 2005Accepted 2 February 2006Available online 6 March 2006

This study analyses women's participation in forestry. The study was carried out with 270women in the Bartın province, located in theWest Black Sea Region of Turkey. By employinga Principal Component Analysis it was found that the most important factors affectingwomen's participation are women's perception related to (1) forest dependence, (2) qualityof cooperatives, (3) quality of Forest Organisation, and (4) forest quality. These four factorsexplained 58% of women's participation. These factors need to be taken into considerationto enhance women's participation in forestry and to achieve sustainable forestry in Turkey.Regression analyses indicate that age, marital status, the rate of population increase andwealth are important variables for explaining variation in levels of participation. Theestimated game theoretic model on women's participation indicates that the sharing offorest benefits amongwomen in Turkey is considerably harmonious, while there is scope forimproving the Forest Organisation, namely by stimulating participation towards a moreeffective management of the Turkish forests.

© 2006 Elsevier B.V. All rights reserved.

Keywords:Women's participationForestryTurkeyPrincipal Component AnalysisRegression analysisGame theoretic model estimation

Jel classification:C31C72Q23

1. Introduction

The involvement of communities in forestry is now a majorcomponent of internationally supported forestry programsand a significant (and increasing) feature of forest policy andpractice in countries throughout the world (Brown, 1999;Warner, 2005, p. 1). The motivation for a better understandingof local needs often came from the fact that any rural initiativecould become more effective in persuading the community

stry of Zonguldak, Karae

s.org, doganatmis@hotma

er B.V. All rights reserved

rather than developing an initiative through a participatoryprocess that addressed locally defined needs, often leading toundesirable outcomes. Currently, participatory approaches,methodologies and tools are widely used (Warner, 2005, p. 5).

Women's survival and that of their household and com-munities depend on access to and control of natural resources,such as land, water, forest and vegetation. They perform themajority of the world's agricultural work, producing food fortheir families, as well as other goods that are sold in national

lmas University, Bartın, Turkey. Tel.: +90 378 2277422; fax: +90 378

il.com (E. Atmiş), isdasdemir@e-kolay.net (I. Daşdemir),

.

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and international markets.Women are traditionally the primeparticipants in both the agricultural and the forestry compo-nents of agroforestry production systems. They have learnedtomanage these resources in order to preserve them for futuregenerations. Yet, women's access to and control of theseresources is far from guaranteed (Pearl, 2003, p. 3). Womensuffer most from environmental disasters and reducedavailability of forest products. It is the women and childrenwho collect fuel wood, animal fodder, decayed leaves andother forest products. Furthermore, they are held responsiblefor tending sheep, goats and other domestic animals owned bytheir families (Fortmann and Rocheleau, 1984; Molnar, 1987;Boo and Wiersum, 2002; CFAN, 2005). Women are alsoincreasingly gaining attention in the forestry professionsince they have entered all levels of forest related work.Their role is quite often different from that of men, and theymay have different interests and roles in a participatoryprocess (Anonymous, 2000). Although this does not necessar-ily translate into an equal opportunity and maybe women'sviews have not yet been heard, it has empowered manywomen and given them the chance to interact with their malecounterparts (Anonymous, 1999).

Traditional gender roles assign different responsibilities towomen and men. This has resulted in political, cultural andeconomic barriers that restrict women's access to naturalresources. For example, women are frequently excluded fromdecision-making. Community leaders may not invite womento meetings related to resource use, or expect only the men topresent their concerns. Lower levels of literacy and educationamong women may further restrict their participation.Government and institutional policies often fail to recognisethe importance of women's access to natural resources. Whileresearch has shown that agricultural productivity increasessignificantly when female farmers have access to land andtechnology, women own less than 2% of all land (Pearl, 2003,p. 3). In addition to the development level of the region andtype of the settlement (rural or urban), gender and socio-economic groups also affect individual's access to basicservices (benefits). The same is true for the rest of the world:women and the poor have less access to basic services(benefits) than men and the rich. This low access makesboth women and the poor disadvantageous. Yet, thedisadvantages aggravate when the individual is a woman,poor and lives in rural areas, since poor rural woman residesat the bottom of the hierarchical ladder with respect toaccessibility to basic services (Toksöz and Şen, 2001).

Women's actions from the local village to the global policy-making arenas are a driving force for change. From the 1975UnitedNations (UN) International Year ofWomen, through theDecade of Women (1976–1985) and the global conferences andsummits of the 1990s, women participated actively to shapeeconomic, social, political, and sustainable development.Throughout the 1990s, women's organisations struggled toput gender on the global policy agenda at key UN InternationalConferences, including the UN Conference on Environmentand Development (Rio-1992), The International Conference onHumanRights (Vienna, Austria, 1993), the International Confe-rence on Population and Development (Cairo-Egypt-1994), andthe fourth World Conference on Women (Beijing-China-1995).At the 2000 UN Millennium Summit, 191 governments reaf-

firmed their commitment to women's empowerment andadopted the Millennium Declaration, agreeing to “promotegender equality and the empowerment of women as effectiveways to combat poverty, hunger and disease and stimulatedevelopment that is truly sustainable.” The Declaration alsoaddresses “the equal rights and opportunities of women andmen” and pledges to “combat all forms of violence againstwomenand to implement theConvention on the Elimination ofAll Forms of Discrimination Against Women” (Pearl, 2003, p. 3).

There are some international agreements emphasising andsupporting the importance of women participation in forestrytoo. In this context, in Principle 20 of Rio Declaration, it isstated that “women have a vital role in environmentalmanagement and development, and their full participationis therefore essential to achieve sustainable development”. InForest Principles it is stated that “the full participation ofwomen in all aspects of the management, conservation andsustainable development of forests should be actively pro-moted” (UN, 2005). Also, the Final Statement of XIth WorldForestry Congress in Antalya calls countries “for promotingparticipatory forest planning and decision-making processesby all interested parties, and enhancing training of forestryprofessionals and field staff, with particular attention to therole of women and youth” (Anonymous, 1997). Similarly, theFinal Statement of XIIth World Forestry Congress in Quebeccalls countries “to encourage collaborative partnershipsinvolving women, forest owners, indigenous people, nongov-ernmental organisations, local communities, industry andpublic agencies” (FAO, 2005).

Rural women in Turkey are not homogenous with regard tosocio-economics, geographic region, socio-cultural factors aswell as age and education. A good socio-economic status ofthe family makes women more powerful in her relations withher husband and the community. The region also mattersbecause the level of development and land productivity arecrucial factors that effects women's involvement inmarketingand access to services. Age is another important factoraffecting participation (Toksöz and Şen, 2001, p. 6). In Turkey,the education level of most of the women living in rural areasis low. Differences in education level influence the people'sview on forests. Uneducated people tend to demand morephysical products of forests than other benefits. The womenliving in rural areas have as an important activity to collectfuel wood and other forest products and tend domesticanimals. They believe that the main benefit of forests is fuelwood and other physical products. In spite of somedifferences between the regions of Turkey, it is generallyobserved that women are absent when forest villagersconflict with the Forest Organisation and they do notcommit as much forest offences as men (Atmiş, 1999, p. 66,2001, p. 232, 2003, pp. 95–96; Atmiş et al., 2005, p. 16).

Participation of women in management of forests inTurkey is an issue, which should be emphasised and not beneglected. Women can play a pivotal role thanks to the theirclose relationship with the forests. However, to achieve this isvery difficult, both because of women's backward status in thesociety and because of traditional practices in TurkishForestry. There are 20,080 forest villages in Turkey and 7.6million people reside in these villages. The majority ofpermanent inhabitants of these villages are children, elderly

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and women, because men (temporarily) migrate to cities forwork. For that reason, women participate in forest activities aswell as domestic work, childcare, agriculture and animalhusbandry.

There are 20.7 million hectares of forests in Turkey. TheState owns the property and manages 99% of these forests.Forest villages have some privileges and rights in forestproducts. Additionally, forest villagers have some beneficialrights such as collecting fuel wood, mushrooms, fruits, leafs,etc. The Turkish Forest Organisation generally appoints mento put these rights into practice, in spite of there not being anyrules and regulation by law. Women are in a situation wherethey are working hard, but women are hardly ever asked fortheir opinions. Moreover, women cannot make their owndecisions in many issues. Men generally benefit from educa-tional programs implemented in forest villages. Also, inscientific research and rural area surveys in Turkey, inter-views are mainly undertaken with men.

The participation of stakeholders needs to be strengthenedfor making the Forest Organisation in Turkey more successfuland to achieve sustainable forestry. The factors affectingparticipation need to be determined to achieve an effectiveand balanced participation of stakeholders. The purpose ofthis study is to analyse women's participation, which is animportant stakeholder of participation, to determine thefactors (dimensions of participation) affecting women's par-ticipation in forestry. The study was carried out with 270women in the Bartın province, located in the West Black SeaRegion of Turkey.

The outline of this paper is as follows. Section 2 discussesthe used materials and methods. This entails a description ofthe study area and highlights the characteristics of thecollected primary data. Section 3 analyses the primary dataemploying a Principal Component Analysis. The derivedfactors are used in a multiple regression analysis. Section 4sets up a game among women competing for using the forests

Fig. 1 –Location of the study

adjacent to their villages. This game is estimated and theresults are discussed. The final section concludes.

2. Materials and method

2.1. Description of the study area

This study has been conducted in the Bartın province, where46% of the total amount of land is forest area. This province isrepresentative for the West Black Sea Region and hasintensive forestry (Fig. 1). The population of Bartın provinceis 184,178. 74% of the population, which is the highestproportion of all 81 provinces in Turkey, lives in rural areasand depend on the forest (SIS, 2000). There are 224 villages inthe boundaries of the Bartın Forest Enterprise and 223 (99.5%)of these are forest villages, and people in these villages benefitfrom the forest either legally or illegally. Because of thesereasons, Bartın was chosen as the study area.

All the forest villages in the Bartın province were rankedfrom the one with the fastest decreasing population to the onewith the fastest increasing population. Depending on thisrank, the villages were divided into 27 groups of eight villages.And, the village with the highest forest area per capita waschosen in each group. In total 8 villages were not included forsampling because one of the 224 villages is not a forest villageand 7 other villages newly emerged from inhabitants ofexisting villages in the period 1990–2000 such that it was notpossible to determine the population changes correctly.Thereupon, the study was implemented in a total of 27 pre-selected villages.

Ten female interviewees from each of the 27 villages wereselected using random sampling. Thus, the study covered intotal 270 women interviewees. To achieve the researchobjectives, a questionnaire was prepared and the trained

area (Daşdemir, 2005).

Table 2 – Personal features of women

Features Frequency %

Age groups15–25 73 27.126–35 57 21.136–45 65 24.146–55 46 17.056+ 29 10.7

Education levels1 Illiterate 68 25.22 Literate (not primary school) 14 5.23 Primary school 159 58.94 Secondary school 24 8.85 High school 4 1.56 University (2 years) 1 0.3

Marital status1 Single 51 18.92 Widow 14 5.23 Married 205 75.9

Number of pregnancy

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interviewers applied it in interviews with 270 women in 2004.The questionnaire included the characteristics of women suchas socio-economic features (i.e. age, marital status, educationlevel, size of the family, number of pregnancies, income),contribution of women labour to the family economy, decisionmaking, types of work by women, standard judgments andopinions about forests, type of participation in forestry,expectations and benefits from forests and the ForestOrganisation, illegal benefits from forest resources, conflictswith the Forest Organisation,membership of cooperatives andexpectations of it, rate of population increase and forest areaper capita in the village.

Information sources for the study include: data obtainedfrom the questionnaires, existing records, the State Instituteof Statistics and Bartın Government. Because the majority ofthe data is qualitative, they are converted to quantitative databy using a statistical scaling method (Kalıpsız, 1988). Forinstance, the variable “benefits from forest resources” (BFR),which has a central role in the game estimation, is convertedinto quantitative data as follows. Women gave scores for eachforest benefit (i.e. wood, chestnut) obtained from forest

0–3 100 37.04–6 103 38.27–9 40 14.810–12 19 7.012+ 8 3.0

Table 1 – Names, labels, and units of the quantitativevariables

No. Names of variable Label Unit Scale

1 Age AGE Year [15–65]2 Marital status MAS – [1–3]3 Educational level EDL – [1–6]4 Number of people in the

familyNPF – [1–12]

5 Number of pregnancies NOP – [0–15]6 Source of family income SIF % [3–40]7 Contribution of women

labour to family incomeCWF Hours/year [0–2056]

8 Number of alternatives forproviding home water

TPW – [0–4]

9 Number of tools for cooking TCB – [0–1]10 Being affected by decision

makingBAD – [1–56]

11 Benefits from forestresources

BFR – [0–559]

12 Standard judgments aboutthe forest

SJF – [0–292]

13 Level of development offorest resourcesmanagement

DFM – [0–53]

14 Sufficiency of goods andservices by the ForestOrganisation

SGS – [0–4]

15 Illegal benefits from forestresources

IBF – [0–3]

16 Membership of forestrycooperatives

MFC – [0–1]

17 Desire to participate andbeing informed aboutforestry activities

DPI – [0–4]

18 Conflicts with the ForestOrganisation

CFO – [0–3]

19 Expected benefits fromvillage cooperatives

EBC – [0–5]

20 Monthly income of family MIF US$ [250–1500]21 Rate of population increase RPI % [−53–41]22 Forest area per capita FAC Ha/capita [2–54]

resources in 1 year. These scores have been collected fromall women, and they have been converted into total scores.Table 1 shows that the value of this variable varies between 0and 559. Similarly, the others qualitative variables areconverted into quantitative variables. In total, 22 quantitativevariables are derived and used in the study (Table 1).

To evaluate all variables simultaneously and, thus, todetermine factors characterising the role of women in relationto forests and the most important factors affecting women'sparticipation, a Principal Component Analysis is used (Harman,1967). Furthermore, the derived factors are used in a multipleregression analysis (Ordinary Least Squares) to explainvariation in women's participation. In addition, a non-cooperative game model (the Simple Threshold Method) isset up to voluntarily participate in the management of forestsadjacent to their villages. In applying these statistical techni-ques, Version 12.0 of the Statistical Package for Social Science(SPSS) is used.

2.2. Characteristics of the collected data

In order to obtain an insight into the composition of theinterviewed 270 women, Table 2 shows the distribution ofinterviewees according to personal features.

Table 2 shows that respectively 27%, 21%, 24% and 17% ofinterviewees are in the age group between 15–25, 26–35, 36–45and 46–55, while 11% is older than 56. With respect to familysize, respectively 37%, 38%, 15% and 7% of the women had 0–3,4–6, 7–9 and 10–12 pregnancies, while 3% had more than 12pregnancies. Typically older women tend to have morepregnancies than relatively younger women. A reason forthis, apart from the age difference can be education, havingknowledge of family planning and the level of development.

Table 3 – Grouping participation according to FAC

Participationgroup

Limit value of FAC (ha) Number of interviewee % of interviewees Name of settlement (village)

Group 1 (lowest) ≤12.25 110 41 Kışla, Kızıllar, Zafer, Bakraçboz, Şahne,Kıranpazarı, Ören, Akgöz, Çayaltı, Uzunöz,Çubuklu

Group 2 (low) 12.26–22.65 50 18 Şahin, Topluca, Kayacılar, Makaracı,Kocaköy

Group 3 (middle) 22.66–33.05 70 26 Yukarısal, Özbaşı, Tarlaağzı, Söğütlü,İbrahimderesi, Bağdatlı, İmamlar

Group 4 (high) 33.06–43.45 10 4 HatiplerGroup 5 (highest) ≥43.46 30 11 Aşağıdere, Yeniköy, Çerde

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The levels of education of the women are quite low. Approx-imately a quarter of them are illiterate and 59% finishedprimary school (5 years of education). Older women tend to beeither illiterate or have a relatively low level of education.

The majority of the interviewees (76%) are married. Thetraditional age to get married is low in the study region. Theportion of interviewees that have been married reaches apercentage of 81% once widows are taken into account. Apercentage of 56% them is influenced by their husband intheir own decision-making, while another 15% of them isinfluenced by their society. The remaining 29% of themmake decisions based on their own knowledge and opinions.The older the women become, the higher the influence oftheir husbands and society on their decision-making. Thelow level of education of older women most probably causesthis.

Table 4 – Principal Component Analysis of nine indicatorsofwomen's participation in forestry in the Bartınprovince,Turkey

Description Code Factor1

Factor2

Factor3

Factor4

Conflicts with theForest Organisation

CFO 0.661 0.401 −0.222 −0.061

Illegal benefits fromforest resources

IBF 0.647 −0.042 0.112 0.277

Desire to participateand being informedabout forestry

activities

DPI 0.639 −0.216 −0.010 −0.330

Being affected bydecision making

BAD −0.029 0.750 −0.076 0.206

Expected benefits fromvillage cooperatives

EBC 0.243 0.571 0.350 −0.042

Membership of forestrycooperatives

MFC −0.210 0.551 0.046 −0.289

Sufficiency of goodsand services by the

Forest Organisation

SGS 0.117 −0.016 0.832 0.057

Level of developmentof forest resourcesmanagement

DFM 0.336 −0.104 −0.514 0.108

Standard judgmentsabout the forest

SJF −0.008 −0.006 −0.023 0.893

Variance explained 17.0% 16.1% 12.6% 12.0%

Rotation method: Varimax with Kaiser normalisation. Rotationconverged in six iterations (N=270).

By grouping the intervieweeswith respect to forest area percapita, it turns out that 41% of interviewees have a forest areathat is lower than 12 ha, while 11% of the interviewees have aforest area that is more than 43 ha (Table 3). Although themajority of the interviewees is a member of the first group(lowest forest area group), the forest area per capita regardingthe average of all interviewees is substantially higher than theTurkish average of 0.34 ha per capita (Geray, 1998). The forestwealth in the study region is high, and so, all groups have anintensive relationship with the forest.

According to Table 3, it can be said that the availability offorests is the highest in the villages Hatipler, Aşağıdere,Yeniköy and Çerde of which forest area per capita are higherthan 33 ha.

3. Results and discussion

3.1. Principal Component Analysis of women'sparticipation

To study factors that explain women's participation inforestry or to determine the most important factors affectingwomen's participation in forestry, a Principal ComponentAnalysis is undertaken on nine participatory indicators BAD,SJF, DFM, SGS, IBF, MFC, DPI, CFO, EBC (see Table 1).1 Table 4shows the result. The first four factors turn out to haveeigenvalueswith a value greater than 1, leading to four factors.

Interpretation of the result in Table 4 yields that the mostimportant component of women's participation is related toforest dependence, explaining 17% of the variance. There arethree dominant indicators of participation (factor loadinglarger than 0.5 in absolute terms). In the first factor womentend to be in conflict with the Forest Organisation, acquireillegal benefits from the forest and they have a high stake inthe forest.

The second factor is almost equally important as the firstfactor, explaining 16% of the variance, representing the qualityof existing village cooperatives, in short the quality ofcooperatives. There are again three dominant indicators ofparticipation here. In the second factor, women tend to behighly affected by decision-making, have high expectationsfrom village cooperatives, and also tend to be a member offorest cooperatives.

1 See also Lise (2000) and Lise et al. (in press).

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The perception of the quality of Forest Organisation is the thirdfactor, explaining 13% of the variation. There are only twodominant indicators of participation in this factor. A highvalue in the third factor indicates women's need for asufficient flow of good and services from the Forest Organi-sation and a good level of development of forest resourcemanagement. The latter participatory indicator has a negativefactor loading due to the fact that most women perceive thelevel of development to be low.

Forest quality is represented by the last factor, explaining12% of the variance. The fourth factor consists of oneparticipatory indicator only, namely a standard judgementconcerning the quality of the forest.

3.2. Multiple regression analysis of women's participation

To explain the driving force behind the four factors ofwomen's participation in forestry in Turkey, we have alsoundertaken a multiple regression analysis. The followingmodel is estimated by using Ordinary Least Squares (OLS):

Factori ¼ constantþ b1AGEþ b2MASb3EDLþ b4NPFþ b5NOPþ b6SIFþ b7CWFþ b8TPWþ b9TCBþ b10BFRþ b11MIFþ b12RPIþ b13FACþ error ð1Þ

Eq. (1) shows that the four factors, which were found withthe Principal Component Analysis, are used as the dependentvariables. All other not yet used 13 variables enter theregression equation as descriptive variables.

Table 1 shows the meaning of the variables, which areincluded in the regression. The result is presented in Table 5.Statistical significant estimates are indicated by stars: ⁎P<0.10,⁎⁎P<0.05, ⁎⁎⁎P<0.01.

Interpretation of Table 5 yields a number of additionalinsights into the process of women participation in forestry.First of all, four variables are never significant in explainingthe variation in participation. This indicates that the level ofeducation, the family size, the level of contribution of

Table 5 – Regression analysis to explain variation in women's p

Description Code Fdepe

PC1

(Constant) −0.566Age AGE −0.007Marital status MAS −0.071Educational level EDL −0.029Number of people in the family NPF 0.038Number of pregnancies NOP 0.005Source of family income (10−3) SIF 0.934Contribution of women labour to family economy (10−3) CWF 0.011Number of alternatives for providing home water TBW 0.024Number of tools for cooking TCB 0.011Benefits from forest resources (10−3) BFR 3.073Monthly income of family (10−3) MIF −0.091Rate of population increase RPI −0.005Forest area per capita (10−3) FAC −0.004

R2 adjusted 0.233

The presented values of five variables (indicated with 10−3) need to be di

female labour to the family income and the forest area percapita have no significant influence in setting the level ofparticipation.

Secondly, more benefits from the forests indicate higherlevels of forest dependence, while areas with a high level ofout-migration are also contributing to a higher level offorest dependence. The level of benefits from the forestsdoes not explain the level of participation in the second,third and forth factor. Similarly, the best chances ofvoluntary participation can be found among the villagerswho depend highly on the forest and perceive the quality ofthe forest as good (Lise, 2000).

Thirdly, according to the second factor, there are sixdrivers for evaluating the quality of village cooperatives.The six drivers are older and married women, providing alow fraction to the family income, providing home water,having a relatively high monthly income (from the hus-band), and facing out-migration from the village. Womenwho possess these six characteristics give value to thequality of village cooperatives.

Fourthly, there is only one driver for the quality of theForest Organisation, namely richer families find the ForestOrganisation important and valuable.

Finally, according the fourth factor, there are five driversfor evaluating the quality of the forest. While we found thatolder and relatively richer women give value to the quality ofvillage cooperatives, younger and relatively poorer womengive value to the quality of the forest. These women aremarried, have children, and they possess cooking tools.

Age is an important variable in explaining variation inparticipation. The level of education tends to be lower for olderwomen. A reason for this is that in the past, the educationopportunities in villages were limited and also the girls werenot allowed to go to school due to prevailing traditions andsocial norms. Older women are mainly interested in collectingforest resources. Young women are willing to participate inand contribute to the process of decision-making, affecting

articipation

orestndence

Quality ofcooperatives

Quality ofForest

Organisation

Quality of theforest

PC2 PC3 PC4

(0.509) −2.613⁎⁎⁎ (0.492) −1.034⁎ (0.583) −0.193 (0.555)(0.008) 0.020⁎⁎⁎ (0.008) 0.011 (0.009) −0.018⁎⁎ (0.008)(0.086) 0.540⁎⁎⁎ (0.083) −0.118 (0.099) 0.296⁎⁎⁎ (0.094)(0.074) 0.055 (0.072) 0.112 (0.085) −0.089 (0.081)(0.031) 0.016 (0.030) 0.005 (0.035) −0.024 (0.034)(0.026) −0.041 (0.025) 0.015 (0.030) 0.054⁎ (0.029)(4.137) −7.976⁎⁎ (3.999) −2.032 (4.736) 3.038 (4.514)(0.109) −0.049 (0.106) 0.142 (0.125) 0.077 (0.119)(0.030) 0.057⁎⁎ (0.029) 0.018 (0.034) −0.003 (0.033)(0.161) 0.019 (0.156) 0.128 (0.185) 0.293⁎ (0.176)

⁎⁎⁎ (0.393) 0.354 (0.379) −0.090 (0.449) 0.247 (0.428)(0.298) 1.080⁎⁎⁎ (0.288) 0.612⁎ (0.341) −0.743⁎⁎ (0.325)

⁎ (0.003) −0.006⁎⁎ (0.002) −0.004 (0.003) −0.001 (0.003)(3.954) −3.584 (3.822) 0.203 (4.527) 1.700 (4.315)

8 0.2841 −0.0044 0.0877

vided by 1000. The values in the brackets denote the Standard Error.

Table 6 – Payoff matrix for the participation game

Villager 2: (contender)

Participate Do not participate

Villager 1:(challenger)

Participate x,x b,aDo notparticipate

a,b y,y

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forestry. Young women make decisions based on their ownopinion, rather than being influenced by their families andneighbours. However, this study cannot provide any conclu-sive answer related to the level of education of women in ruralareas, because this variable is not significant in all of the fourconsidered regression equations.

The contribution of women to family income is anothervariable, which is not significant in all of the consideredregressions and is not a useful indicator for stimulatingparticipation. Conflicts with the Forest Organisation occuragain and again in spite of obtaining illegal benefits andthe willingness to participation in forestry. To preventconflicts, there is a need to improve the socio-economicsituation of forest villagers by the State and the ForestOrganisation.

Table 7 – Assigning women's level of participation

Level of participation ofchallenger (θ)

Level of participation ofcontender (ϑ)

Payoffgroup

‘Participate’ ‘Participate’ X‘Participate’ ‘Do not participate’ B‘Do not participate’ ‘Participate’ A‘Do not participate’ ‘Do not participate’ Y

4. Game estimation

4.1. The participation game among women in forestry inTurkey

For studying the opportunities of local people in general, andwomen in particular, to voluntarily participate in the man-agement of forests adjacent to their villages, we set up a non-cooperative gamemodel. The strategy is to choose the level ofparticipation in forestry. Here participation means how avillager perceives the local organisation in the village tomanage an adjacent forest. A participating villager adheresto rules that are prevalent in the village. This participation isawarded with the right to (partially) access the forest fromwhich they appreciate the benefits (=their net payoff). Let usrefer to this situation as the participation game.

Taking these considerations into account, we can dem-onstrate the mechanism of this game by a metaphoricaltwo-person two-strategy representation. In order to formal-ise possible conflicts, which can emerge between villagers,let us restrict the analysis to two equal villagers {1,2}. In thecase with n villagers contesting for access to the forest, wecan distinguish between villager 1, the challenger, andvillager 2, the contender, which is composed of all othervillagers contesting for the same forest. For that we need toassume that the challenger interprets the actions of othervillagers as a simultaneous move. Hence, we are dealingwith a 1 versus n−1 persons game (see also Lise, 2001, 2005;Lise et al., 2001; Lise and Bakker, 2005; Lise et al., in press).

The simplest form of such a game consists of only twopersons, who have a choice between two alternatives: toparticipate or not. When both villagers participate they obtainx. When one villager participates, while the other does not, thesingle participant keeps the rules as formulated during the

village meetings, obtaining b, while the other cheats on theserules, reducing the protection of the forest, obtaining a. This‘cheating’ can be detected through ‘social fencing’, where therule-abiding villager spots cheating. This can be reported tothe forest guard. Finally, when both deviate, rules are notadhered to by both villagers, obtaining y. Table 6 shows theresulting payoff matrix.

A possible outcome of this game is a prisoner's dilemma,where the dominating strategy is to not participate anddeplete the forest, while it would lead to collective betterresults when both villagers would participate, keeping theregeneration rate of the forest optimal. Hence the followinginequality could hold:

a > x > y > b ð2Þ

It is also possible that there is no conflict, leading to othertypes of games.

4.2. Technical description of the game estimationprocedure

For estimating the participation game we need to construct atriple (πi,θi,ϑi), where πi is the payoff for villager i, measured asthe benefits from forest resources (the variable BFR as shownin Table 1), while θi is the strategy for villager i, measured asthe level of participation (chosen as the first, second or thirdfactor as derived in Section 3.1). The strategy of the con-tenders, ϑi, which is the strategy of all other villagers asperceived by the challenger, can be derived by taking theperception of the quality of the forest, which is the fourthfactor, as derived in Section 3.1. The fourth factor is in a waythe perception of the villagers of the joint action of all othervillagers.

To interpret the value of the strategy, it is useful tonormalise the strategy of the challenger θi and the strategyof the contender ϑi. In general, variable si can be converted intoa fraction between 0 and 1 as follows:

x̃i ¼si−minkaN Sk

maxiaN sk−minkaN skfor all iaN ð3Þ

It is possible to assign the payoffs into four payoffgroups by taking 0.5 as the threshold value. We definevalues of θ and ϑ above 0.5 as participative behaviour in thesense that a villager has a participatory attitude, whilevalues of θ and ϑ below 0.5 indicates that a villager is notparticipating. This simple way of splitting the payoffs isreferred to as the Simple Threshold Method (STM) (Lise etal., in press). Assigning the payoffs is done as shown inTable 7.

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

PC1 - Forest dependence

PC

4 -

Qua

lity

of th

e fo

rest

A X

BY

Fig. 2 –Scatterplot of the perception of forest dependence and forest quality.

794 E C O L O G I C A L E C O N O M I C S 6 0 ( 2 0 0 7 ) 7 8 7 – 7 9 6

Finally, the payoffs can be calculated by applying formula(4), where |X| denotes the number of observations in payoff-group X:

a1jAj

X

iaA

pi; b1jBj

X

iaB

pi; x1jXj

X

iaX

pi; y ¼ 1jYj

X

iaY

pi

4.3. Results

The Simple Threshold Method as explained in the previoussection is applied to derive the participation games. In order toobtain insight in the assignment of payoffs to payoff groups,the choices of the challenger and the contender are plotted inFigs. 2–4. The choice of the challenger, θ, represents respec-tively the perception of forest dependence (factor 1), quality ofvillage cooperatives (factor 2) and quality of the ForestOrganisation (factor 3). The choice of the contender, ϑ,represents the perception of the quality of the forest; a highϑ/θ is a positive perception, while a low ϑ/θ means a negativeperception. Figs. 2–4 show the result for the Simple ThresholdMethod where a division into four payoff groups is indicatedby the thick lines.

Interpretation of Figs. 2–4 already leads to an interestingoutcome, namely that themost frequent occurrence ofmutual

(4)

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4

PC2 - Quality

PC

4 -

Qua

lity

of th

e fo

rest

A

Y

Fig. 3 –Scatterplot of the perception of qua

participation is found with respect to forest dependence. Thisis shown in the figures by the concentration of data at theupper-right cell (=X) in Fig. 2. B is the right lower cell, A is theleft upper cell and Y is the left lower cell (this is also indicatedin the figures by putting an upper-case letters in the four cells).

The game estimation results, using the primary data asexplained in Section 2, are presented in Table 8.

In interpreting the results as presented in Table 8, we find aPareto game (participation is a dominating strategy for bothplayers and also leads to a Pareto optimal outcome) both forthe perception of forest dependence and the quality ofcooperatives in the village. This matches well with thescatterplot of the strategies in Figs. 2 and 3 and it meansthat the payoffs are homogenously distributed. Finding aPareto game for forest dependence also confirms the outcomeof the first regression equation, namely that the variable“benefiting from the forest” is positively correlated with forestdependence.

The third game differs, however, from the first two games,namely we find a chicken's game for the game on theperception of the quality of the Forest Organisation. Thechicken's game implies that the optimal strategy of thechallenger is to choose the opposite of the strategy of thecontender. Mutual participation is Pareto optimal, but not a

0.6 0.8 1

of cooperatives

X

B

lity of cooperatives and forest quality.

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

PC3 - Quality of Forest Organisation

PC

4 -

Qua

lity

of th

e fo

rest

A X

BY

Fig. 4 –Scatterplot of the perception of quality of Forest Organisation and forest quality.

795E C O L O G I C A L E C O N O M I C S 6 0 ( 2 0 0 7 ) 7 8 7 – 7 9 6

stable outcome. A policy implication of this result is that thereis strong contrast in women's perceptions to the quality of theForest Organisation. Improvements in the Forest Organisationare needed to improve participation.

5. Conclusions

This study has found factors characterising the role ofwomen in relation to forests in Bartın representing theWest Black Sea Region of Turkey. The data obtained from270 interviewees are evaluated by statistical methods. Theanalyses indicate that the most important factors affectingwomen's participation in forestry were found as thewomen's perception concerning (1) forest dependence, (2)quality of cooperatives, (3) quality of Forest Organisation, (4)forest quality. These four factors explained 58% of women'sparticipation in forestry. These factors need to be consid-ered to enhance women's participation in forestry activitiesin the Bartın province of Turkey.

The perception of the forest quality depends on age(younger perceive better), marriage (married women perceivebetter), number of pregnancies (women with many childrenperceive better), tools for cooking (women that have thesetools perceive better), and the monthly family income (poorerwomen perceive better). The socio-economic compositionchanges rapidly in villages near the city, namely their

Table 8 – Estimated participation games

a b x

Forest dependence 137 214 284(48) (35) (175)

Quality of cooperatives 246 212 308(200) (9) (23)

Quality of Forest Organisation 269 197 241(89) (23) (134)

The numbers in the brackets denote the number of observations within tusing Eq. (4). Payoffs are expressed in a unitless valuation; a larger numb

populations tend to grow and the economic opportunitiesare better, reducing the pressure on women to undertakephysical labour, leading to a more comfortable life. Neverthe-less, in rural areas, the responsibilities and tasks of womenincrease, because men migrate to cities for work.

Age, marital status, rate of population increase andwealth are important variables for explaining variation inlevels of participation. The level of conflict concerning thesharing of forest benefits among women in Turkey isconsiderably low, while there is scope for improving theForest Organisation to stimulate participation and a moreeffective management of the Turkish forests. These factorsneed to be taken into consideration to enhance women'sparticipation in forestry and to achieve sustainable forestryin Turkey.

A model of participative management needs to bedeveloped in order to improve forestry in Turkey. It isimportant to take the role of women in relation to the forestinto consideration.

Acknowledgement

We are thankful to the participation of 270 women in theBartın province in this study. We also thank Banu BayramoğluLise for helpful comments and English–Turkish translations.Furthermore, we are grateful to two anonymous referees foradditional comments. Remaining errors are ours.

y Payoff order Name of the game

124 x>b>a>y Pareto game(12)186 x>a>b>y Pareto game(38)185 a>x>b>y Chicken's game(24)

he payoff group, from which the payoff is derived by taking averageser represents a higher payoff.

796 E C O L O G I C A L E C O N O M I C S 6 0 ( 2 0 0 7 ) 7 8 7 – 7 9 6

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