ADVISOR:-BADASSA WOLTEJI (PHD

AMBO UNIVERSITY SCHOOL OF GRADUATE STUDIES DEPARTMENT OF ECONOMICS HOUSEHOLD’S WILLINGNESS TO PAY FOR DEBELE FOREST CONSERVATION; THE CASE OF DIRE INCHINI DISTRICT, WEST SHOA, OROMIA, ETHIOPIA BY FIKADU ADUGNA BITIMA A MASTER THESIS SUBMITTED TO THE DEPARTMENT OF ECONOMICS IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTERS SCIENCE IN DEVELOPMENT ECONOMICS ADVISOR:-BADASSA WOLTEJI (PHD) AMBO, ETHIOPIA APRIL, 2021  APPROVAL SHEET Submitted by PG Candidate Name Signature Date Fikadu Adugna Bitima ___________ ______________ Approved by 1. Advisor Name Signature Date Badasa Wolteji Cala ____________ ______________ 2. Co-advisor Name Signature Date ___________________ ________________ _________________ 3. Co-advisor Name Singnature Date _______________ _____________ ______________ 4. College/Institute Dean Name Signature Date ____________________ _______________ _______________ 5. Head, Department Name Signature Date __________________________ _______________ ______________ 6. Director, School of Graduate studies Name Singnature Date _________________ ___________________ _____________ Certification Sheet Ambo university School of graduate studies Certification sheet A thesis research advisor, I hereby certify that I have read and evaluated this thesis prepared under my guidance byBadassa Wolteji (PHD)entitled ‘‘Household’s Willingness to pay for Debele forest conservation; the case of dire inchini district, west Shoa, Oromia, Ethiopia’’. I recommend that it be submitted as fulfilling the thesis requirement. Badassa Wolteji (PhD.) _ __________________ Name of Major Advisor Signature Date ________________________ ___________________ ___________________ Name of Co-Advisor Signature Date As mentioned of the Board of Examiners of the M.Sc/MA. Thesis open defense examined. We certified that we have read and evaluated the thesis prepared by Fikadu Adugna Bitima and examined the candidate. We recommend that the thesis be accepted as fulfilling the thesis requirements for the degree of Master of Science/Art in Development Economics Chair person Name Singnature Date Indalew Bongase _________________ _____________ Internal examiner Mohamed Idris _________________ _____________ External Examiner Gemechu Mulatu ______________ ACKNOWLEDGEMENTS First of all, I would like to express my deepest gratitude to my major research advisor, Badassa Wolteji (PHD)AmboUniversity for his unreserved advice, guidance, and constructive criticism during my entire study and research period. Without his encouragement, insight and professional expertise, the completion of this work would not have been achieved. I would also like to thank the enumerators (Mr. Gosa Alemu, Mr. Jima Degaga, Mr. Birahanu Angasu, and Mr. Tadele Geramu), Mr. Fekede Gemachu, Mr. Mideksa Babu who assisted me during data collection and their contribution on thesis andsmallholder farmers and development agents in the surveyed district who volunteered to provideinformation making it possible to achieve this research. I would also like to thank different officesincluding the Dire Inchini Agricultural and Natural Resource Office for providing me with their records andfacilitatingmyfieldwork.Lastly, I would like to extend my sincere Dire Inchini Livestock Development office. Finally, I would like to thank my parents and family for all their support. Without their moral support and backup in any aspect, it would have been only mere wish to accomplish my academic and professional career. LIST OF DIAGRAM ix ABSTRACT xi 1. INTRODUCTION 1 1.1 Background of the study 1 1.2. Statement of the Problem 3 1.3 Objectives of the study 5 1.3.1The specific objective of the study 5 1.4. Research Questions 5 1.5 Significance of the study 5 1.6 Scope of the study 6 1.7. Organization of the study 6 2. 1. Theoretical Literature 7 2.1.4 Definition of Terms and Concepts of willingness to pay 11 2.2.1 Empirical Review 13 2.2.2 Forest Policy of Ethiopia 16 3.1 Description of the study area 19 3.2 Sample size determination and Sample techniques 20 3.3 Method of Data collection 22 3.4 Method of Data Analysis 22 3.5 Model Specification 23 3.5.1 Contingent valuation method 23 3.5.3.2. The Censored Regression (Tobit) Model 25 3.6. Defining Variables and Working Hypothesis 26 3.6.1. Dependent variables 26 3.6.2 Explanatory Variables: 26 4.1 Descriptive Results 30 4.1.1 Descriptive summary of households` characteristics 30 4.1.2. Demographic and physical characteristics 32 4.2 Willingness to Pay 34 4.3 The probit regression model result analysis 35 4.4 Tobit regression model result analysis 37 5.1. Summary and Conclusions 42 5.2. Recommendations 43 6. REFERENCE 45 Appendix A 48 Appendix B 54 Appendix C 60 LIST OF ACRONYMS CSA Central Statistical Agency CV contingent valuation CVM contingent valuation method DUV Direct use value FAO Food and Agricultural Organization of the United Nations FDRE Federal Democratic Republic of Ethiopia FGD Focus Group Discussion GDP Gross Domestic Product IUV Indirect use value MOA Ministry of Agriculture NGO Non-Governmental Organization NUV None use value OLS Ordinary list square PFM Participatory Forest Management UNDP United Nation Development Program WTA willingness to accept WTP willingness to pay LIST OF TABLE page Table .1 sample of house hold and sample size ----------------------------------------------------------19 Table.2 Summery of hypothesized variable ---------------------------------------------------------------13 Table 3 Descriptive summery of WTP---------------------------------------------------------------------36 Table 4 Contingent valuation response --------------------------------------------------------------------41 Table 5 Bivariate probit output result ---------------------------------------------------------------------43 Table 6 Censored Tobit model result ----------------------------------------------------------------------45 Table 7 Household’s income generation ------------------------------------------------------------------47 LIST OF DIAGRAM ` page Diagram 1 the conceptual frame work of the study -----------------------17 LIST OF FIGURE page Figure 1 the map of the study area --------------------------------19 LIST OF APPENDICES page Questionnaire ------------------------------------------------------------------------------68 Questionnaire in afan oromo -------------------------------------------------------------69 Stata output ---------------------------------------------------------------------------------70 ABSTRACT There are many study done on household’s willingness to pay but there was gaps like benefit that households can generate according to their participation or income generation source to do so there must be methods which can increase the households perception. This makes the researcher to studyabout, identifying factors affecting household’s willingness to pay for forest conservation and to know the income that households can generate from forest conservation.The contingent valuation method, Descriptive statistics, probit models and Tobit model was employed. Two stage sampling procedure was used to select sample households fordata collection. A total of 231 sample households were selected by using stratified random sampling method. Interview schedule was used to collect data from household heads quantitative data collected from primary. The majority of (86%) surveyed households have willingness to pay and the rest (14%) disagreed toPay for forest conservation. The results indicates that, education of the household ,income of household’s, household’s as source of income, Family size, initial bid value distance from the forest significant and positive or negative correlation with households WTP. The finding also gets that without compromising the conservation of the forest the households can generate income from bee keeping fuel wood and Gum rising.The result of this study suggests there is a good chance of success if proper collection method is introduced. And these charges should take into consideration both ability and willingness to pay.Therefore, by taking the importance of the resource for the society and the household’s WTP, the policy makers need to focus on identified factors in designing strategies for the conservation of forest. . Keywords:-CVM; Debele Community forestHousehold’s; probit Model; Tobit model; WTP  1. INTRODUCTION Background of the study Concern with the supposed increasing scarcity of natural resources, and the possibilityof running out of strategically important raw materials or energy sources, is by no means new. Worries about resource scarcity can be traced back to medieval times in Britain and have surfaced periodically ever since. The scarcity of land was central to the theories of Malthus and the other classical economists. In the 21thcentury, fears about timber shortages in several countries led to the establishment of national forestry authorities, charged with rebuilding timber stocks(Winberg, 2017). The total global forest area has declined by 3%, from 4128 million ha in 1990 to 3999 million ha in 2015 (FAO, 2015 and Keenan. 2015). The forest area decrease from 7.3 million ha per year in the 1990s to 3.3 million ha per year between 2010. The natural forest area declined from 3961 million ha to 3721 million ha between 1990 and 2015, while planting forest (including rubber plantations) increased from 168 million ha to 278 million (Keenan, 2015). The Africa total forest area is declining from 705 million ha in 1990 to 624 million ha in 2015. Due to both natural causes such as drought, fire, storms and disease, and human cause such as clearance for agriculture, over-exploitative timber harvesting, the expansion of settlements, and infrastructure development, natural forest area is declined within 25 years. But, planted forest area increased from year to year because of expansion of reforestation, forestation and other forest rehabilitation and restoration strategies through community participation (FAo, 2015 and Keenan, 2015). There is significant deforestation in Ethiopia. The main driver is small scale farm land expansion andunsustainable fuel wood consumption (CRGE, 2011). However, the government of Ethiopia is making utmosteffort to reverse deforestation on one hand while rehabilitating degraded forest lands on the other. Amongthe measures taken the most prominent include: adoption and up-scaling of participatory forest managementapproach to most natural forest blocks, watershed based a forestation, area exclosures, institutional reform byestablishing a new Ministry of Environment and Forests, and legal framework improvement both at Federaland Regional Ethiopia is also keen in implementing REDD+ to generate incentives for improved forestmanagement. These all changes are improving and expected to improve forest management outcomes in Ethiopia (FAO, 2020). Similarly, rehabilitation of forests through forestation, agro forestry, building of soil and water conservation structures, reforestation and area enclosures with participatory forest management practices is another conservation effort that the government is implementing (Temesgen, 2015). Currently, degraded forest rehabilitation activities are implemented through community participation at Participatory Forest Management (PFM) (Alemayehu, 2015) and participatory enclosure management (Eshetu, 2014). The government has shifted a policy towards forest management and rehabilitation from state centered approach to participatory or community centered approach for sustainable management and utilization of forests (Alemayehu, 2015). Participatory Forest Management (PFM) started in Ethiopia during 1990 with the help of NGOs (FARM Africa, SOS Sahel and others) to address deforestation thereby managing forest in a sustainable manner (UNDP, 2012 and Temsgen., 2015). It was first introduced to Ethiopia 31 years ago at Chilimo and Bonga forests as a pilot test; the approach is expanding to cover more and more hectares of forest across the country (UNDP, 2012). In Ethiopia, PFM is well adopted in 2010 including regional governments and at every District offices (Winberg, 2017). Since deforestation rates in Ethiopia historically correlate with the expansion of agricultural land (FDRE, 2017),increasing household participation in forest conservation practice enables tominimize the pressure on the remaining forest of the country in line with this the proportion of new land for agriculture that is taken from forest will decrease from 70 to 55% (FDRE, 2015). Two million hectares of pastureland will be afforested up to 2030 and 1million hectares of degraded will be reforested (FDRE, 2011). Having a way to measure the magnitude of external cost on use of resources helps environmental protection advocators and policy makers greatly in their effort to create mitigation measures and conservation mechanisms the most widely used approaches for decision of public policy instruments to mitigate environmental impacts has been the contingent valuation method (CVM), CVM been widely accepted by academics and policy makers for valuation of resources environmental goods, and services In the case of Debele forest even if an attempt is make to conserve and estimate the economic value of forest using acceptable environmental valuation techniques bygovernment and none government. They fail to estimate the economic value of forest and the protection because of the complexity of forest management decision. Yet, in recent decades, concerns have arisen about the proper valuation of environmental resources and progress has been achieved in developing valuation methods. But an economists use the concept of willingness to pay (WTP) to determine consumers WTP for improved and avoiding deterioration of environmental resource (Agudelo, 2011).But to the researcher knowledge Most of actions are focusing on participatory forest management. Debele forest has many importance in that; it is among source of living for different wild life and human being, It provides different benefits to the population; for example soils for agriculture, trees for timber, fuel wood, reeds, recreation and scientific activities.The current Debele forest is deteriorating continuously due to different human activities that have destroyed forest causing erosion which carry away agriculture land and destroying biodiversity habitat. The government, through the forest law 542/2007, has established protection measures to protect forest in general. In this study therefore, an attempt was to estimate the household’s Willingness to pay both in cash and labor in for conservation of Debele Community forest. Besides, the study assessed that how households, can generate an income from participating in forest protection. 1.2. Statement of the Problem There are many research conducted on household’s willingness to pay for forest conservation practices that are implemented through community participation. Those studies have their own gaps and a few of them are stated as follows. Lack of linkage among actors (Alemayehu, 2015), the absence of clearly defined property rights and user rights (Semeneh, 2015), gender disparity in participation and lack of active community participation and the absence of rules and regulation to penalize absenteeism (Eshetu. 2014) are major constraints that affect rehabilitation practice. But, having rules and regulation on penalties in monetary terms and in kind can increase community participation on development activities (Haregeweyn, 2012).are some of them We can also see the studies within the outers as world as our country Ethiopia as well as oromia regional state. But as Local area that Debele Community there is no evidence that shows about willingness of household’s to pay for conservation of community forest. When some of studies and their gaps as fallow’s. The studies conducted on the factors affecting community participation on forest management at PFM in Ethiopia address only the levels of participation of forest users association or groups towards forest managements (Abay, 2013).Similarly, studies conducted on the determinants of collective action on bamboo forest management do not elicit the forest rehabilitation activities performed by the community (Semeneh, 2015). In addition, studies conducted on the factors affecting house hold willingness to pay for forest improvement and conservation Ethiopia address only the levels of participation of forest users association or groups towards forest managements ( Abay, 2013),here the study didn’t identify the community gain either as compensation or other form of income. Similarly, studies conducted on the determinants of collective action on forest management do not elicit the forest rehabilitation activities performed by the community (Semeneh, 2015). Due to socioeconomic (education, income and wealth) and perception on benefits obtained and forest degradation effects (Mengistu and Mekuria, 2015), institutional (property rights, incentives and extension services) (Semeneh, 2015) and others factors. However, all above studies do not elicit the socio-economic factors (education, benefits obtained and others, physical factors (distance of forest from home) and demographic factors (age and family size) towards the conservation practice. In general, those studies do not elicit Conservation of community forest. Perception of communities in natural resources management can be viewed from the angles of perceived economic, social and environmental benefits. Again those studies do not address the income that households can generate from participation in degraded forest improvement and Conservation of forest.All the mentioned studies mainly focused on the supply side of forest management with little or no reference to the demand side. Therefore, the above gaps initiate the researcher study that how can increase the perception of household’s toward the value and importance of Debele community forest? Beside conservation of forest by valuing the forest using contingent valuation method. After they know the value of forest, then the research assess what are determinants of households’ willingness to pay for conservation of Debele forest? Also identify how community can generate income and economic contribution of participation of forest conservation? 1.3 Objectives of the study The general objective of the study was to assess household’s willingness to pay for conservation of Debele forest at Direinchini District West shoa Zone of Oromia National Regional State. 1.3.1The specific objective of the study To identify the maximum amount that Household’s willingness to pay for Conservation of Debele Community forest. To explore factors affecting a household’s willingness to pay for conservation of forest. To know how community can generate income from their participation in conservation of forest. 1.4. Research Questions What is the maximum amount that Household’s willingness to pay for improvement and Conservation of Debele Community forest? Which factors are mainly affecting a household’s willingness to pay for improvement and conservation of forest? How community can generate income from their participation in conservation of Debele forest? 1.5 Significance of the study Improvement and conservation of forest rehabilitation is a global phenomenonand needs collaboration of nations and mankind in the world. This study have been conducted at local level and also considered willingness of house hold to pay in degraded forest conservation practice of limited area. First, study at grass root level house hold willingness to pay for forest conservation by using contingent valuation methods response to this will help to design intervention that have greater impact at higher level policy that seek to community based PFM at the local level. Having information about factors affecting household’s willingness to pay activities in degraded forest improvement and conservation from different direction and location is important to design entire based of community based PFM strategy at zonal and district level. Secondly, the study willreveals the constraints face House hold participation in degraded forest conservation practice made by house in PFM at local level helps to look at better alternatives to achieve plan of the government to perform sustainable forest management. Thirdly, the findings of this study will help policy makers, development practitioners and researchers with developing. The study will helps the government and concerned body to identify salient household’s features that would increase the targeting and subsequent success of forest improvement and protection activities in the study area as well as in other area with similar characteristics. 1.6 Scope of the study This study only identifies the factors affecting house hold Willingness to pay Improvement and conservation of forest and their income generation source.With regard to the geographical coverage, this study will delimit to 5 (five) Dire Enchine District kebele those have contact to the forest and particular households those live around Debele Forest. 1.7. Organization of the study The thesis has five chapters. Chapter one consists back ground of the study statement of the problem, research questions, objectives, significance of the study, scope of the study and organization of the thesis. Chapter two presents review of theoretical and empirical evidences to the study. Chapter three discusses research methodology (description of the study area, data types and sources, methods of data collection, sampling techniques and methods of data analysis, working hypothesis and definition of variables) of the study.Chapter four presents result and discussions descriptive a analysis, and econometric analysis. chapter five presents summary and recommendations. 2. LITERATURE REVIEW 2. 1. Theoretical Literature 2.1.1 Contingent valuation method (CVM) It is a direct means of estimating the economic benefits of an improved water supply. Using this method, one simply asks how much the consumer is willing to pay for a given level of service. It is a survey based method, where people are asked directly how much money they would be willing to pay or accept to maintain the existence of environmental resources such as forest.CVM has been increasingly advocated by Economists and sector specialists as a useful tool for gathering reasonably accurate data about how much a household can afford and is willing to pay for particular water and sanitation options presented to them. The CVM involves asking people directly what they would be WTP or WTA compensation for change in preferences and the method is called contingent valuation for it is contingent on the hypothetical market. The CVM is preferred to the revealedpreference methods for it includes both use and non-use values and survey responses to WTP or WTA hypothetical questions go directly to the monetary measures of utility change (Perman, 2013). 2.1.2. Applicability, Strength and Weakness of CVM A major strength of CVM is that, because it does not rely on actual markets or observed behavior, it can in theory be applied to any situation, good or service. They remain one of the only methods that can be applied to option and existence values, and are widely used in combination with other valuation method, in order to supplement or cross-check their results (Emerton ., 2014). The same source further indicated that one of the biggest disadvantages of CVM is the large and costly surveys, complex data sets, and sophisticated analysis techniques that it requires. Another constraint arises from the fact that they rely onhypothetical scenario which may not reflect reality or be convincing to respondents. CVM require people to state their preferences for ecosystem goods and services. They are therefore susceptible to various sources of bias, which may influence their results.The most common forms of bias are strategic, design, instrumental and staring point bias. Strategic bias: occurs when respondents believe that they can influence a real course of events by how they answer WTP questions. Critics suggest that because there is no collection of real money, respondents who are ‘pro-environment’ will exaggerate their bids for environmental preservation so long as they believe that the survey will actually have an impact on policy or outcomes. CVM Respondents may for instance think that a survey’s hypothetical scenario of the imposition of a water charge is actually in preparation. (Bennett and Carter 2014) indicated that one way of attempting to disguise the strategic bias is the use of the dichotomous. Design bias: this relates to the way in which information is put across in the survey instrument. For example, a survey may provide inadequate information about the hypothetical scenario, or respondents may be misled by its description. According to (Smith,2006), careful development of survey instruments (through initial preparatory work, focus groups, cognitive interviews, and pretests); conscientious implementation of field work; and rigorous econometric analysis that link the data to underlying theoretical models (e.g., utility functions) can help reduce design bias in a CV study. Instrument bias: Arises when respondents react strongly against the proposed payment methods. Respondents may for instance resent new taxes or increased bills. Controversial payment vehicles should be avoided in favor of those most likely to be employed in real life to elicit payment for good in question (Georgiou, 2017). Starting point bias:- occurs when the starting point for eliciting bids skews the possible range of answers, because it is too high, too low, or varies significantly from respondents’ WTP. (Kartman, 2011) gives three possible sources for this bias. Lack of clear understanding of the good or poorly defined good, significant difference between respondents actual willingness to pay and the starting value suggested (if used), and assumption of the respondent that the true value of the good is around the starting point.( Smith,2006)suggests that the use of proper elicitation questions and proper bids with an adequate range can reduce the starting point bias. Closed-ended questions may have very small starting point bias. The iterative bidding method is especially prone to this bias. (Whittington, 2010) also suggests that background information and focus group discussions would help determine the appropriate range of the bid values. The rule of thumb is that the lowest bid should be low enough that most of the respondents will accept it, while the highest bid should be high enough that most respondents will reject The major steps involved in using CVM include: Designing and administering a CV survey that elicits individual’s value for a good or service. According to (Mitchell and Carson 1989), in this step of a CVM, the questionnaire consists of three parts. The first part of the questionnaireincludes a hypothetical description of the terms under which the good or service is to be offered to the respondent. The second part tries to determine how much the respondent values a good or service (elicitation of WTP or WTA). The third part includes questions about socio-economic and demographic characteristics of the respondents including his/her family. Analyzing WTP responses–this involves the calculation of frequency distribution, cross tabulation of WTP responseswith socio-economic characteristics and other variables and the estimation of the bid function. Estimating aggregate benefits and total revenue-calculating the total economic benefit (total WTP) which can be calculated by multiplying the population by the mean WTP. Evaluating the CVM exercise (validation tests) –undertaking validity test to determine whether the CVM results are acceptable or not.Although a number of researchers have employed the CVM, using such survey method has some basic problems in the sense that survey respondents could give biased information The fact that the method is based on hypothetical scenario rather than actual behavior is the source of enormous controversy. Thus, the biases mentioned above systematically understate or over state true values. To reduce these biases, the questionnaire for this study is designed with somehow detailed description of the proposed improvements of the scenario.CV Questionnaires Design In designing CV questionnaire, initial preparatory activities should provide adequate information that will feed into designing a preliminary version of a CV survey instrument. The preliminary CV instrument should have a reasonable CV market scenario that takes into account the specific locality, various water supply sources and conditions, cultural and socioeconomic situations of the communities, as well as payment mechanisms for the proposed service improvement. Then, it should be refined using focus group discussions and pretesting in the field (ADB, 2017). Each component in the questionnaire fulfils an important role and taken together they introduce the respondent to the context and relevant background in progressively more detail, and also gather information about the respondent and their understanding of the scenario which is needed to report the results or to establish the validity of the response. Some questions may test whether key aspects of the scenario have been understand, while other questions about the degree of familiarity with the good in question will reveal whether the respondent is a user or a non-user. The questionnaire must ensure that three specific conditions are upheld in order to ensure validity of the results: the non-market good must be carefully defined; the scenario must provide a plausible means of payment; and there must be a plausible mechanism for making the trade-off between consumption of private goods and the good in question (Arrow et al., 2011). CV survey instruments vary from study to study depending on the specific context. According to (ADB 2017) a CV survey instrument should have the following modules : An introductory section, briefly describing background and purpose of the survey Module Questions on demographic, socioeconomic profile of the households, and profile of the respondents interviewed Module Questions on current condition of the good under question Module CV market scenarios followed by questions eliciting WTP values Module Contingent valuation (CV) elicitation techniques The most widely used elicitation formats in CV surveys are open-ended, bidding game, payment card and single (double) bounded dichotomous choice (Hanley,2014). Open-ended format–a CV question in which respondents are asked to provide the interviewer with a point estimate of his/her WTP; it has the advantage of relative computational easiness and counter starting point bias. But the method is associated with a large number of respondents’ non-responses and protests zero bids. (Mitchell and Carson 1989) further argue that the method is difficult since respondents faced to pick a value out of the air without some form of assistance Closed-endedapproaches(dichotomous choice question)-asked respondents whether they would pay a stated amount for the good in question by providing intervals in which the respondents WTP lies. This method is advantageous over open-ended question format in eliciting WTP because of the simplicity of “yes “or “no” answers for the respondents and thus reduce incentives for strategic responses (Bateman 2012). It has also advantage of being much more similar to the choice that individuals are asked to make in real markets when faced by market prices. However it suffers from starting point bias, shortage of information, reducing efficiency and requirement of large sample to estimatebenefits as maximum WTP is not directly obtained from this format. This study uses both closed ended (single-bounded) and open-ended formats. Bidding game–is a CV question format in which individuals are iteratively asked whether they would be willing to pay a certain amount, by raising (lowering) the amount depending on the respondents WTP for the previous offered amount. It has a better efficiency than closed-ended format because it has a potential to elicit the respondents maximum WTP (Cummings, 1986) and that the iterative process helps the respondents to fully consider the value of the good in question (Hoehn and Randall,2011). But the method exhibits very strongstarting point bias and may be boring to the respondents and thus they may give answers only to avoid additional questions. Payment card -is a CV question format in which individuals are asked to choose a WTP point estimate (or an interval) from a list of values predetermined by the surveyors and shown to the respondent on the card. This method is better than open-ended format as it could be simpler for the respondents and large proportion of responses could be obtained. However, the method requires the respondent to be literate that makes it of little use in developing countries, where a considerable proportion of the population is illiterate Definition of Terms and Concepts of willingness to pay Value: can be understood as willingness to pay to avoid loss, or willingness to accept for compensation Household:-consists of a person or group of person irrespective of whether related or not, who normally live together in the same household and housing units and have common cooking and eating arrangement (CSA, 2015) Willingness to pay (WTP): An economists use the concept of willingness to pay (WTP) to determine consumers WTP for improved and avoiding deterioration of environmental resource (Pearce, 2002).willingness to pay is defined as maximum amount of income the individual will pay in exchange for an improvement in circumstances or the maximum amount he will pay to avoid a decline in circumstances Forest-:Food and Agricultural Organization of United Nations (FAO,2015) at Global Forest Resources Assessments (FRA, 2015) data definition of forest is land spanning more than 0.5 hectares with trees higher than 5 meters and a canopy cover of more than 10 percent, or trees able to reach these thresholds in situ. Forest improvement: Re-establishing the productivity and some, but not necessarily all, of the plant and animal species originally present. For ecological or economic reasons, the new forest may include species not originally present. In time, the original forest’s protective function and ecological services may be re-established (David and Don, 2003). Improvement is making the land useful again after a disturbance. From forest perspectives, it defined as the recovery of forest functions and capacity in order to supply products and services. Improvement does not necessarily re-establish the pre disturbance condition, but does involve establishing geological and hydro logically stable landscapes that support the natural ecosystem mosaic (WRI, 1999).improvement is defined as the process of supporting the recovery and management of a degraded ecosystem (both the structure and the function) to a close approximation of its condition prior to disturbance (Mulugeta, 2006). Restoration differs from rehabilitation in that restoration is a holistic process not achieved through the isolated manipulation of individual elements. While restoration aims to return an ecosystem to a former natural condition, rehabilitation implies putting the landscape to a new or altered use to serve a particular human purpose (WRI, 1999) does not include land that is predominantly under agricultural or urban land use 2.1.5. Theory of Pareto optimality In the case of welfare economics the main purpose of any economic activities is to increase the wellbeing of the responding individuals or economic agents. In this study, the basic assumption will be an individual makes a decision to maximize their utility from their participation in improvementand conservation of the forest. Following this, measurement of the economic values of forest protection and improvement is depends on the effect of the hypothesis project on households welfare A Pareto criterion is the best way to explain welfare. It isindicating that policy changes make at least one person better off without making any one worse off. Besides, Pareto improvement noted public intervention is good for efficient resource allocation. If the cost of the public action is less than the sum of the benefits from a public action, it is considered worthwhile by the criterion (Haab , 2012). The applied side of modern welfare economics works a variant of the Pareto criterion by trying to find ways to place a dollar value on the improvement and deterioration from environmentalchange (Alem, 2019). The study will identify the maximum community participation the advantage the community gate from improvement and conservation of forest. This allows the calculation of net gain or loss from a policy change, and determination of whether the change is potentially Pareto improvement or not. Changes in environmental quantity and quality may affect individual‘s welfare. Because environmental change may lead to changes in prices an individual pay for marketed goods and inputs. Moreover, it may change the quantities or qualities of environmental goods such as forest resource,(Mason, 2011). The basic strategy for environmental valuation is the co-modification of the services that the natural environment provides; it serves to assess individual and group priorities and trade-offs in the case of scarce commodities. The most commonly used approach is based on the concept of Total Economic Value (TEV). In this approach, an impact on environmental resources is broken down into different categories of values. The idea behind this is that the resource or service comprises of various attributes, some of which are tangible and readily measured, and others are considered less tangible and difficult to quantify. These values are namely the direct use value (DUV), the indirect use value (IUV) and the non-use value (NUV). In Hekssian welfare measure estimation of the economic benefits of the environmental goods requires identification of the actual demand function for the improvement of the environmental goods. However, it is very tricky to estimate the actual demand curve since it requires accurate market data. Therefore, to fill this problem we should use an alternative method which requires the creation of hypothetical market scenario. The alternative method is that a CVM and this method can generate the WTP data, which will be used to value the forest improvement and protection without having to estimate the actual demand curve (Hekssian, 2014) 2.2.1 Empirical Review A study by Garrod and Willis estimated the mean WTP of the public for the non-use biodiversity value of remote coniferous forests in Britain using contingentranking method and contingent valuation in the form of double bounded elicitationmethod. It estimated the public‘s WTP for a number of forest management standards that could be adopted to improve levels of biodiversity in remote upland coniferous forests, which the respondent would never visit. The authors estimated the value of marginal changes in biodiversity of remote upland coniferous forests, rather than the total value of biodiversity in remote upland coniferous forests as a whole. The value for increasing biodiversity of these forests using contingent valuation at the margin was £10 to £11 per household per year for biodiversity for a 30% increase of the area of this forest type. Whereas, the value for increasing biodiversity of these forests using a contingent ranking method was £0.30 to £0.35 per household per year for a 1% increase in these forests. A study by (Demel, 2010)determined visitors’ willingness to pay for conservation of forest resources at Gunung Gede Pangrango National Park (TNGP). The results indicate that income, gender (male) and residential (urban) were the significant factors that influencing the visitors’ WTP for the entrance fee to TNGP here externalize the willingness to visitors not local community how they can participate in resource conservation. A study by Carlson applied a contingent valuation method to estimate the economic values of community plantations trees in the highlands of Ethiopia (Carlson, 2014). A discrete-continuous elicitation format was applied. The survey covered a total of 1520households from both East Gojam and South Wollo of Amhara region. The mean WTP from sample respondents is estimated to 10 ETB3 for the closed-ended responses. The study found that there is a problem in applying a closed ended elicitation format because it would exaggerate the respondent willingness to pay for community plantations trees. Besides, the analysis of the bid function shows that women in villages without any existing community plantation are significantly more interested in the establishment of a plantation than men. The authors recommended that separate interviews are made with heads and spouses when it comes to valuation of local natural resources. The result of the study also showed that the aggregate willingness to pay vary dramatically between villages. Therefore, the concerned body needs to develop good tools for the selection of locations for community plantations if they seek to maximize their contribution to welfare. Tegegne also applied this method to elicit people‘s valuation for environmental protection in terms of both cash requirement and labor contribution. He concluded that households in the study area are willing contribute in terms of labor than cash. Moreover, education, age, sex and family size turned out to be factors affecting the willingness to pay in term of labor(Tegegne, 2007) The study found that the mean WTP for eucalyptus tree from open ended, single and double bounded elicitationformat are computed at 22.79 ETB, 45.81 ETB and 38.06 ETB, respectively. Using similar procedure the mean willingness to pay for indigenous trees using open, single and double bounded probit model were also computed at 22.14ETB, 44.31 ETB and 26.96 ETB, respectively. The author found that the mean WTP from all elicitation methods were greater for eucalyptus than for indigenous trees. This could be indigenous trees are not, in most cases, fast growing like eucalyptus tree. The results of study also show that age, types of ownership, access to credit, the value of livestock owned by the family and bid are significant influences household WTP for eucalyptus and indigenous trees. The study concludes that labor was the most preferred payment vehicle than cash and kind A questionnaire survey was conducted on 148 respondents from six peasant associations surrounding the natural forest(Tefera, 2016). The mean willingness to accept for a single household was 44.6 birr per year. Moreover, about 72% of the respondents gave the value of the forest at a price of 30birr or more per year while 18% of the respondents agreed to pay nothing assuming that they have traditional rights to the land and/or have low level of income. The bid function analysis suggested that household’s income has minimum influence on the WTPTherefore, it can be concluded that even the poor households were willing to pay the average values in terms of time or labor contribution to save the natural forest. On the other hand, community valuations for forest resources in the catchment do not vary much in magnitude when the payment vehicle was changed from cash to labor contribution. A study by (Badege, 2011), examines the determinants of Household‘s willingness to pay for forest conservation practices in the highlands of Bale, southeast Ethiopia oromia regional state, The study found thateducation level of the household head, perception of forest degradation problems, Size of farmland; conservation undertaking in the past, parcel prone to erosion and farm area under crop are factors that affect farmers WTP for forest conservation practices But here the study does not identify the maximum amount that household willing to pay and the income that local community can get from their participation of forest conservation. It may be observed from these empirical studies that there are large numbers of direct and indirect benefits of forests. Using CV method for valuation across regions, different estimates of economic values of tangible and intangible benefits are obtained. The variations in the estimates could be partly on account of different socio-economic variables and the scope of the studies. Furthermore, the literatures above suggested that contingent valuation method is viable techniques to quantify house hold WTP for non-marketed goods in the developing countries. Thus the given literature above provided some sound footings to this study to value households WTP for Debele forest improvement and protection in Dire inchini District. 2.2.2 Forest Policy of Ethiopia Ethiopia has been experiencing multiple challenges in governing its forest and related environmental resources for quite a long time (Alemayehu, 2014). Formal forest policy started in Ethiopia during the brief period of Italian annexation (1936 - 41). Italians issued various forest laws and regulations and instigated the first structured forest administration called MiliziaForestale(Forest Militia). The incidence of forest deforestation and management of forest was the driving factor for development of forest policy in Ethiopia. During Derge regime, non-participatory agricultural land demarcation for tree planting and induced land reform made for expansion of forestlands through established autonomous forestry institution Forest and Wildlife Conservation and Development Authority (Melaku, 2003). Under FDRE regime, the 1995 constitution particularly vested the power to enact laws for the utilization and conservation of land and other natural resources, including forestry, to the federal government. Within this broader policy framework, forest management authority has been legally shared betweengovernment agencies at different administrative tiers (Alemayehu, 2014). And also, the regional governments have been developing their own forest development, conservation and utilization which are consistent with federal government proclamation. The country is developing forest policy for sustainable utilization and management of forest. The current Forest Development, Conservation and Utilization Proclamation No. 542/2007 are developed for conservation and utilizations forest in a sustainable manner (FNG, 2007). Forest development, conservation and utilization plans shall be formulated to allow the participation of local communities in the development and conservation of the forest and in the sharing of benefits from the development of state forests. The local community may be permitted to keep bee hives, produce spices, forest coffee, forage and the likes in a protected forest by providing them forest development and conservation training and technical support. Based on current legislation enacted, PFM initiatives in Ethiopia developed for communities in and around forested areas can be part of the solution for reducing deforestation and regeneration of forest resources (MOA, 2012). 2.2.3 Conceptual Framework The study will focus on assessing contingent valuation methods as well as identifying factors affecting house hold willingness to pay for forest improvement and conservation. There is a need to examine the interrelationship and interactions of various factors revolving around the decision of household towards willingness to pay in degraded forest conservation. (Sumit, 2012). Diagram 1 shows the conceptual frame work of the study Source: Adapted from (Edward ,2017) 3 RESEARCH METHODOLOGY 3.1 Description of the study area Dire Enchine district is found in Oromia regional state, West Shewa Zone at the distance 40 km from zonal capital city of Ambo at South West direction and 155km from Addis Ababa at west direction. It was bounded by Toke Kutaye district in East and North, Jibat district in the West and South West Shewa Zone specifically Amaya district in south direction. At present Dire Enchine district have 20 kebeles and 1 urban village. The district comprises 20 peasant associations and each kebele hosts one farmer training center. In particular, in the study area primary schools were fairly distributed throughout the district; therefore, children from every household get access. There are one senior secondary school and health services are available in the district. Geographically the study area was located (situated) in mid highlands of Ethiopia and central oromia region lying between 08045′N and 08 0 77′ N latitude and 37 0 38′and 370 62′E longitude and ranges between the lower Altitude 2050m to 3028 m the higher at an average of 2540m meters above sea level (masl). In general the physiographic features of the study area have various land forms such as plateaus, hills, plains and valley. TulluRoggee, Tullusaqee, TulluuDaballee and Gafare Local named important mountains and Balesa , UrufaDonjo and Farisi were the local named plateaus of the district respectively ( source: DEDAO 2015). The district has 20(twenty) ruralkebeles and 1 urban municipality .Among these kebeles the study areas focused on (5) five; which are ArfinjoDega, WaldoHinde,BuyamaDebelle, BuyamaDalfo and BuyamaRoggee.The study will conduct in Debele Forest is 214 hectares and located in 175 km far from Addis Ababa Oromia region west shoa dire Inchini District. Figure 1Study area Source from Dire inchini District rural land use 3.2 Sample size determination and Sample techniques A two -stage sampling technique was used when selected sample respondents. In the first stage 5 rural kebeles was purposively selected out of the 20 kebeles based on their livelihood are more attached to the Debele forest than other rural kebeles In the second stage out of total 3798 population 231 household was selected by using stratified random sampling method. The data will collect using face to face interview with the heads or working or working members of the households. The author and five local enumerators was administered survey. By using a type of stratified random sampling called uniform stratified random sampling. If a population from which a sample is to be drawn does not constitute a homogeneous group, stratified sampling technique is generally applied in order to obtain a representative sample (Kothari, 2004). Hence, total sample size of the households’ were determined following (Kothari,2004) sample size determination; which is applicable when the population size is finite and population is heterogeneous Assumptions to Determine Sample Size: 1. Degree of confidence (Z) 1.96 will be 95%, is the probability that the confidence interval includes the true population parameter and to be worked out from table showing area under normal curve. 2. Margin of error (𝝴) 5%, the percentage point from which margin of error is different from the true population value. 3. Level of significance 5%, is the probability of rejecting the null hypothesis by the test when it is really true. 4. P = 0.8, sample proportion (probability of getting the responses) 5. q = 0.2 (q= 1-p) the probability of not getting the responses 6. N=3798 total population and n is sample size n=231 Table 1. Sample frame and sample size determination Name of kebele Total house hold Number of Sample House hold Arfinjo /Dega 76 Bu/Roge 53 Bu/Miju 39 BU/Dabele 32 Bu/Dalfo 31 Total 3798 231 Source: ((Kothari, 2004) and own computation Method of Data collection The study was gathered Quantitative primary data accompanied by a face to face interview. Focus group discussion and key informant interview will also make as part of data collection method for qualitative primary data for econometrics data analysis. Moreover, the study from secondary journals, books and agriculture office of the Dire Inchini District. Similarly, we were collected quantitative data employing collection of data through questionnaires; the administration method is questionnaire in two sections. The first section incorporates demographic, socioeconomic and institutional variables, perception of respondents about the benefits of the forest, and forest rules and enforcement mechanisms. The second section contains contingent valuation scenario and household’s WTP for the conservation of forests. The questionnaire will translated into the local language (Afaan Oromo) to make easy the data collection process 3.4 Method of Data Analysis For the sake of data analysis, the study was used Descriptive statistics,Contingent valuation method and econometric techniques. Descriptive analysis use for statistical analysis while, econometric part use to investigate the determinants of household’s willingness to pay for conservation of the resource and their payment levels simultaneously using Heckman’s two-step model. Variables, which determine household’s willingness to pay for conservation of Debele community forest, will analyze through this model. In this part STATA 14 software will employ to determine the coefficients of the variables whichare significant to the model under consideration and to test the statistical significance relationships between the determinants and the dependent variable Model Specification Contingent valuation method The study was employed CV method to elicit households WTP for forest resource protection. There are about four major CV surveys, elicitation methods, namely payment cards, discrete choice (single bounded dichotomous choice), discrete choice CV with follow-up questions (double-bounded dichotomous choice) and open ended. However, due to limited experience the payment card approach is not used especially in rural areas of developing countries (Venkatachalam, 2014) including our country Ethiopia. It is easier for respondents to make willingness to pay decisions than open-ended questions (Bennett and Carter, 1993). However, the double-bounded dichotomous choice format is better than single-bounded in three ways. It makes clear bounds on unobservable true WTP and sharpens the true WTP, and hence efficiency gains (Haab and McConnell, 2012). Finally, the double-bounded dichotomous choice format is very vital to collect more information about WTP of each respondent‘s (Hanemann and Arrow 2011). Therefore, this is why researcher plans to employ the double-bounded dichotomous choice following Closed-ended approaches (dichotomous choice question) format to elicit households WTP. 3.5.2. Statistical The role of statistics in research is to function as a tool in designing research, analyzing its data and drawing conclusions (Kothari, 2004).In fact there two types major of area of statistics that descriptive statistics and inferential statistics. The study was used descriptive statistics for the sake data analysis; Descriptive statistics such as percentage mean and standard deviation will used to explain the different socio-economic characteristics and other aspects of the sample respondents. 3.5.3. Econometric analysis After Collection data was taken to software package STATA version 14 and analyze using percentages, frequency, mean, probit and Tobit econometric model. The nature of the dependent variable determines the type of econometric model. Consequently, the objective of this study is to examine the determinants of households’ maximum willingness to pay in the Improvement and conservation practices of forest. 3.5.3.1 Probit model Ordinary linear regression model econometric analysis is widely accepted to analyze the relationship between the dependent and explanatory variables (Aldrich and Nelson, 1984). In OLS analysis the dependent variable is a continuous variable, while the explanatory variables can be either dummy or continuous variables qualitative independent variable. However, when the dependent variable in a regression model is binary (0, 1) the analysis can be carried out using either linear probability model, logit and/or probit models (Pindyck and Rubinfeld, 1981). But, the results of linear probability model may face the following problems. Firstly, the linear probability model may generate predicted values out of the interval zero and one, which can be greater than zero while probability lies between zero and one. Second, the coefficient of determination (R2) is likely to be much lower than one and it is questionable to use R2as measure of goodness of fit (Gujarati, 2004). The third problem with linear probability model is that the partial effect of any explanatory variable is constant (Maddala, 1992). The limitations of the linear probability model can be solved by applying either logit or probit models or both (Amemiya, 1981). The two models generate predicted values between 0 and 1, which follow the basic principles of probability. The main difference between logit and probit is that the conditional probability approaches zero or one at a slower rate in logit than in probit model (Gujarati, 2004). Secondly, the error term in the logit model are assumed to follow the standard logistic distribution, whereas in probit model error term is assumed to follow the standard normal distribution. Thirdly, the probit model works well for multivariate models than logit model. However, in most cases the two models are statistically similar (Park, 2008). This statistical similarity between the two models makes a choice of the models depends on the availability and flexibility of computer program, personal preference and experience (Ibid). Therefore, in this study probit model will use to determine the factors that are affecting the WTP of households. Following (Cameron and Quiggin 2004), the probit model can be specified as: --------------------------------------------------------------(1)       2