Master’s Thesis Economic Contribution of Forest Products to Rural Livelihoods in Northern Mountainous Villages, Vietnam M144763 TRAN ANH DUC Graduate School for International Development and Cooperation Hiroshima University September 2016 TABLE OF CONTENTS TABLE OF CONTENTS i LIST OF FIGURES iii LIST OF TABLES iii ABSTRACT 1 INTRODUCTION STUDY OBJECTIVES LITERATURE REVIEW 3.1 Economic contribution of forest products 3.2 Determinants of household engagement in forest activities 3.3 Forestland devolution in Vietnam 11 STUDY AREA 13 METHODS 17 5.1 5.1.1 Household survey 17 5.1.2 Forest survey 22 5.2 Data collection 17 Data analysis 23 5.2.1 Economic contribution of forest products 23 5.2.2 Determinants of household engagement in forest activities 24 5.2.3 Biological status of household planted forests 26 RESULTS 27 6.1 Household characteristics 27 6.2 Household cash income 30 6.3 Detailed household forest cash income 33 6.4 Determinants of household engagement in forest activities 36 i 6.4.1 Determinants of household forestland and plantation area 37 6.4.2 Determinants of household absolute and relative forest income 38 6.5 Biological status of household planted forests 40 DISCUSSION 44 7.1 Economic contribution of forest products 44 7.2 Determinants of household engagements in forest activities 46 7.3 Limitations of this study 49 CONCLUSIONS AND POLICY IMPLICATIONS 50 ACKNOWLEDMENT 54 REFERENCES 55 APPENDICES 59 ii LIST OF FIGURES Figure 1: Map of the study area 13 Figure 2: Distribution of household forestland, plantation area, absolute forest income and relative cash income in 2014 36 Figure 3: Tree species diversity 41 Figure 4: Diversity in tree trunk diameter 42 Figure 5: Diversity in tree height 42 LIST OF TABLES Table 1: Demographic and land use information of the study area 14 Table 2: House mean characteristics by income quartiles 27 Table 3: Mean household absolute cash income per aeu by income quartiles and income sources in 2014 (USD) 30 Table 4: Mean household relative cash income per aeu by income quartiles and income sources in 2014 (%) 32 Table 5: Mean household absolute forest cash income per aeu by income quartile and forest income sources (USD) 34 Table 6: Mean household relative forest cash income per aeu by income quartile and forest income sources (%) 35 Table 7: Tobit results for determinants of household forestland holding and plantation area in 2014 37 Table 8: Tobit results for determinants of household absolute and relative forest cash income in 2014 39 iii ABSTRACT Title of the Master’s Thesis Economic Contribution of Forest Products to Rural Livelihoods in Northern Mountainous Villages, Vietnam Student ID Number M144763 Name of the Student Tran Anh Duc Main Academic Advisor Professor Nakagoshi Nobukazu Economic importance of forest products to the rural livelihoods has been enlightened by a significant number of empirical studies However, current literature often focuses on the proximity of natural forests, which are, in most of the cases, under the management of communities or states Household managed forests, where local people often actively engage in forest plantation, have been being promoted in developing world for the sake of both poverty alleviation and forest conservation Yet, evidences about economic significance of forest products as well as factors determining household decisions on forest activities in such setting remain limited This study captures the economic contribution of forest products to household income in the context of household managed forests by analyzing a dataset of 308 households in two villages of Bac Kan province, located in the northern mountainous region of Vietnam Household income is measured in cash income per adult equivalent unit, and comparisons among cash income quartiles as well as income sources are performed by ANOVA tests and post-hoc tests In addition, determinants of household engagement in forest activities are examined by Tobit models Equally important, a forest survey is also conducted so as to investigate basic biological status of household planted forests Results show cash income from forest products accounts for about 20% of household cash income, which surpasses cash contribution of all other livelihoods but that of livestock cash income and off-farm wages In addition, although higher absolute forest cash income is witnessed in short-run better-off group, no significant difference is seen in the relative forest income among cash income quartiles Importantly, among forest products, timber is the biggest contributor Tobit models demonstrate positive correlations of cropland area with forestland holding as well as plantation area Furthermore, older-headed families, although having larger forestland and plantation area, derive less cash income from forest products and show less dependency on forest cash income Meanwhile, education level of the household head is negatively correlated with forestland area, absolute forest income and relative forest income Finally, the biological status of household planted forests is concluded to be undiversified Only seven species are found, and two fast-growing species, Magnolia conifer and Acacia hybrid, account for more than 90 percent of the sample Tree height and tree trunk diameter show concentrations in low-value classes due to relatively similar and short plantation durations among households Findings of the study function as an empirical support for poverty reduction based household managed forests Correlation analyses from Tobit models prove the viability of a combination between agriculture and forestry as an economic development policy However, increasing education level are potential obstacles for the current forest-based development Hence, new high-return forest products which are attractive to people of all education levels need developing Last but not least, diversification of planted tree species should be taken in consideration INTRODUCTION Relationships between forests and rural livelihoods have been being investigated worldwide for the sake of forest-based poverty alleviation Evidences from various regions have proved the economic importance of forest sources to the rural poor Quantitatively, contribution of forest products to household income, on a global average, is reported at approximately 22 percent (Angelsen et al., 2014), with the poor are generally more reliant on forest income than the better-off (Babulo et al., 2009; Cavendish, 2000; Rayamajhi, Smith-Hall, & Helles, 2012; Vedeld, Angelsen, Bojö, Sjaastad, & Kobugabe Berg, 2007) In addition, there are ample attempts to model factors that influence household dependency on forests as well as household decision-making for forest related activities (e.g Fisher 2004; Adhikari et al 2004; Rayamajhi et al 2012; Sikor & Baggio 2014; Babigumira et al 2014; Ashraf et al 2015) Results show that many household characteristics are significantly correlated with forest-related decisions as well as forest income Nonetheless, most of the study sites have so far concentrated on state or community managed forests, where environmental products from natural forests often play a key role In a result of their global-scale study, Angelsen et al (2014) report that among 22 percent contribution of forest sources to household income, 21 percent is from natural forests and only percent belongs to plantation Meanwhile, in the context household-based forests management, where active plantation is prevalent, little is known In fact, planted forests managed by households are increasing rapidly, especially in developing regions (FAO, 2006) Accordingly, on global average, proportion of planted forest area managed by smallholders rose nearly threefold in 15 years, from 12% in 1990 to 27% in 2000 and to 32% in 2005 This ratio far exceeded that of corporate ownership, which by contrast witnessed a downward patterns Moreover, the dramatic rising importance of smallholders was particularly seen in East Asian and some South East Asian countries These numbers demonstrate clearly that planted forests managed by households is an emerging type of forest management, offering a compelling contextual setting forest poverty relationship studies Similarly, in Vietnam, studies on economic contribution of forests are clustered in the proximity of natural forests, which are under state or community management (e.g Mcelwee 2008; Viet Quang & Nam Anh 2006) Whereas, FAO reported a significant increase in national smallholder ownership of forest plantation to 64% in 2005, which was more than double public ownership (FAO, 2006) Allocation of forestland to household has been being promoted for decades in Vietnam Because of a weak management of State Forestry Enterprises (SFEs) and a need for productive land of local people in disadvantaged regions in the 1980s, forestland ownership was shifted gradually from the state to individuals (i.e households) (Sandewall, Ohlsson, Sandewall, & Sy Viet, 2010; Sikor & Nguyen, 2007) Such forestland devolution is aimed to achieve both poverty reduction and conservation of forest coverage Nonetheless, economic contribution of available products from household-managed plantation forest remains ambiguous Inconsideration of this inadequate understandings, the study aims at quantitatively evaluating the economic benefits from household-managed forests using a dataset of 308 households generated from a survey in poor mountainous villages of Vietnam Moreover, Tobit models are utilized so as to examine the determinants of household engagement in forest activities Last but not least, biological status of household planted forest is investigated via a forest survey The rest is organized as follows After study objectives and research questions are clarified in section 2, section provides a review of literatures about economic contribution of forest products as well as studies on factors affecting household involvement in forest activities Study area and methods are described precisely in section and section respectively Section presents results from statistical analyses Section discusses, and section concludes and gives policy implication for decision-makers STUDY OBJECTIVES With a view of examining the relationship between rural livelihoods and household-managed forests, the study is to achieve three objectives as the followings: Objective 1: To quantitatively evaluate the economic contribution of products from household managed forests to rural livelihoods in mountainous villages of Vietnam Objective 2: To identify determinants of household’s engagement in forest activities Objective 3: To investigate biological status of household planted forests In order to achieve the aforementioned objectives, the study is designed to answer following research questions: Question 1: To what extent products from household managed forests contribute to household income in mountainous villages? Question 2: Among household characteristics, what have significant impacts on household forestland holding, plantation size and forest income? Question 3: How is the biological status of planted forests managed by households? 3.1 LITERATURE REVIEW Economic contribution of forest products A range of quantitative studies on economic importance of forests have emerged in the last two decades While some of them mainly focus on environmental products from forests, some are designated to capture all forest-related sources from non-cultivated, processed products, plantation to forestry wages Forests offer a range of products for people living in the proximity, such contribution is however often omitted by national economic datasets (Cavendish, 2000) Moreover, the relationship between the poor and forests are controversial as forest sources have both the advantages and disadvantages for poverty alleviation (Angelsen & Wunder, 2003) Based on those arguments, researchers started to comprehensively quantify economic role of forestrelated income Cavendish (2000), utilizing a panel data collected in Zimbabwe, demonstrates that environmental sources from forests account for about one third of total rural household income In addition, environmental income is more important for poorer households with approximately 40 percent of their total income coming from non-cultivated sources Meanwhile, larger absolute environmental income is witnessed in the richer groups Not only is Cavendish’s work one of the first publications to report the contribution of environmental goods, it does introduce methods to quantitatively evaluate income from those easily omitted products In particular, evaluation difficulties often lie in products that are not traded or battered on the market According to Cavendish’s methods of evaluation, implicit prices for those products are either household assigned values, whenever they are possible, or close and locally-traded substitutes In addition, for the sake of comparability of income across household, income per adjusted adult equivalent unit (aeu) is proposed Another pioneering and more forest-oriented study is conducted by Fisher (2004) Using data collected in rural Malawi, the author sheds light on the substantial reliance on forest income, representing about 30 percent Savings How was the household savings compared with that in 2012? What is the amount of increase/ decrease At the end of 2014 Savings deposit in financial Savings in cash at home institutions (VND) 1= increase, 2= decrease, 3= unchanged/ little change At the end of 2012 Savings deposit in financial Savings in cash at home institutions (VND) (VND) (VND) MICROFINANCE STATUS Has anyone in your household taken a loan from VBSP so far? Which program of VBSP did you borrow money from? Is anyone in your household taking loan from other MFIs? MF status (select one) Yes (Case 1) Go to No Go to (code) Yes (Case 2) No (Case 3) Case (member in VBSP) Case (member in other MFIs) Case (non-member) VBSP’s Program 1=Poor Households Program 2=Near-poor Households Program 3=Disadvantaged Students Program 4=Job Creation Program 5=Program for Business and Production Households Living in Extremely Disadvantaged Areas and Communes 6=Safe Water and Rural Sanitation Program (code) (code) ( Go to 4) ( Go to 5) ( Go to 6) 7=Extremely Disadvantaged Ethnic Minority program 8=Housing Support Program for the Poor 9= others (specify) If your household belongs to case 1, please answer these questions a For loans from VBSP Purpose of loan Household When did Loan (Code) Loan term member's you start amount (month) ID borrowing? 2.1 2.2 2.3 (VND) b For loans from other sources 1a Household member's ID Do you have another borrowing source so far? (0=No, If yes, Please specify code) When did you start borrowing? 1a & 1b Other lending sources 1=Vietnam bank for agriculture and rural development (AGRIBANK) 2=Co-operative of Vietnam/ Central people's credit fund (Co-op Bank/CCF) 3=NGO Microfinance institutions (NGO MFIs) 4=Other Commercial Bank 5=Private Money lender 6=friends 7=relatives 8=Others (specify) Purpose of loan (Code) 2.1 2.2 2.3 Interest rate (%) Are you on repayment process now? (1 Yes No) 6a Loan amount (VND) Loan term (month) Interest rate (%) Are you on repayment process now? (1 Yes No) Purpose of loan 1=Agricultural activity 2=Livestock breeding 3=Forestry activity 4=Fishery activity 5=Self Business Which program did this loan belong to? (code) 6=Education 7=Health 8=House building 9=Buying durable goods 10= Water and Rural Sanitation 11=Others (specify) VBSP’s Program 1=Poor Households Program 2=Near-poor Households Program 3=Disadvantaged Students Program 4=Job Creation Program 5=Program for Business and Production Households Living in Extremely Disadvantaged Areas and Communes 7a Did the loan require collateral? (1 Yes No) 6=Safe Water and Rural Sanitation Program 7=Extremely Disadvantaged Ethnic Minority program 8=Housing Support Program for the Poor 9= others (specify) If your household belongs to case 2, please answer these questions 1a Purpose of loan Which MFIs and Household When did Loan (Code) other source did you member's you start amount borrow money? ID borrowing? 2.1 2.2 2.3 (VND) (code) If your household belongs to case 3, please answer these questions 1b Have you ever taken Household When did a loan so far? Purpose of member's you start (0=No, If yes, please loan (Code) ID borrowing? specify code) 1a & 1b Other lending sources 1=Vietnam bank for agriculture and rural development (AGRIBANK) 2=Co-operative of Vietnam/ Central people's credit fund (Co-op Bank/CCF) 3=NGO Microfinance institutions (NGO MFIs) 4=Other Commercial Bank 5=Private Money lender 6=friends 7=relatives 8=Others (specify) Loan amount (VND) Purpose of loan 1=Agricultural activity 2=Livestock breeding 3=Forestry activity 4=Fishery activity 5=Self Business 6=Education 7=Health 8=House building 9=Buying durable goods 10= Water and Rural Sanitation 11=Others (specify) 6a Loan term (month) Interest rate (%) Are you on repayment process now? (1 Yes No) 6a Loan term (month) Interest rate (%) Are you on repayment process now? (1 Yes No) 8a Main reason 1=didn’t meet requirements ２=didn’t need to borrow money ３=complicated procedure ４=Others (specify) 7a Did the loan require collateral? (1 Yes No) 7a Did the loan require collateral? (1 Yes No) 8a Why don’t you join MFIs? (code) HOUSEHOLD INCOME AND EXPENDITURE SURVEY IN 2014 A FOREST NET INCOME IN 2014 Non-timber forest products income in 2014 Product Bamboo Bamboo shoot Firewood Other, specify (3+4) Total Production Unit Own use Sold Price per unit in 2014 (VND) (1*5) Gross value (VND) m3 kg kg Income from forest management in 2014 Management area (ha) Annual income per unit (VND) Income from the latest harvest of timber products Forest area Forest species Harvested Tree age number year Total harvested yield Total (VND) Unit Price per unit (5*7) Total value B AGROFORESTRY AND CROPS INCOME IN 2014 Income from agro-forestry and crop net income in 2014 (4+5) Production Total production Crops Unit area (ha) 1st crop Kg Rice 2nd crop Kg Corn Kg Cassava Kg Sweet potato Kg Banana Kg Own use Sold Lending and borrowing agricultural products in 2014 Lending Product 2.1.Amount 2.2.Borrower 2.3.Location of (code) (code) (code) borrower (code) Products 1=rice 2=corn 3= sweet potato 4= other, specify Borrower/ Lender 1=Relative 2=Neighbor 3=Friend 4=Other, specify Location 1=in the hamlet 2=in other hamlet but in the village 3= in other village but in the district 4= other, specify 3.1.Amount (code) Price per unit in 2014 (VND) (2*6) Total value (VND) Borrowing 3.2.Lender 3.3.Location of (code) borrower (code) C LIVESTOCK INCOME IN 2014 Income from livestock at the end of 2014 Livestock Number of Number of individuals in individuals 2012 in 2014 Meat Pig Breeder Meat Buffalo Breeder Meat Cow Breeder Meet Chicken Egg Meat Duck Egg Meat Swan Egg Other D AQUACULTURE INCOME IN 2014 (3+4) Total Unit Own use production (6+7) Production Unit Own use Sold Price per unit in 2014 (VND) Kg indv kg indv kg indv kg egg kg egg kg egg Sold Price per unit in 2014 (VND) (1*5) Gross value (3*8) Total value (VND) E ANNUAL WAGE INCOME IN 2014 Household Type of work member’s ID (code) Type of work Regular salaried/wage employee: 31=in public sector (government employee), 32=in agricultural sector 33=in forest sectors 34=in other sectors Number of working days per month Number of working months per year Daily/monthly wage (VND) Total income (VND) Business Business Temporary wage labor: 41=in public works, 42=in agricultural sector, 43 =in forest sector 43=in other sectors F OWN BUSINESS NET INCOME IN 2014 Business 1 Type of business Gross income Total costs Net income G OTHER INCOME SOURCES IN 2014 Type of income Remittances Support from government, NGO or organization Significant gifts/ support from friends/ relatives Payment for forest services Compensation from logging or mining company Pension Other, specify Total Total amount received H LIVING EXPENDITURE Expenditure and frequency to go to hospital in 2014 ID How many times did he/she get medical treatment in 2014? (including medicine shop) Children aged years old and under Type of the most frequent medical treatment (code) Health expenditure in 2014 (VND) Elder ages 6o years old and over The member who got medical treatment regularly due to disease/injury Total expenditure Note: If respondent doesn’t remember healthcare expenditure per person, fill in total annual expense Type of medical treatment 1= medical shops; 2= hamlet nurses; 3= village healthcare centers; 4=district hospitals; 5= provincial hospital; 6= central hospital Expenditure in education in 2014 ID Were household member attending Education school in 2014? level (1= Yes; answer 3-6 (code) 2= No; answer 7) Situation of school currently attending (last attended) Location Educational expenses of the Tuition fee Books and school 1= monthly stationary (code) 2= annually (annually) (VND) (VND) Books and stationary (annually) (VND) Main reason why the child was not attending school (code) Total annual expenses Current education level 0=pre-schl 5=class 1=class 6=class 2=class 7=class 3=class 8=class 4=class 9=class 10=class 10 11=class 11 12=class 12 13= college 14= university 15= others, specify Location of the school 1= within the village 2= outside the village but within the district 3= outside the district but with the province 4= in other province 5= in foreign country Other living expenditure in 2014 Type of expenditure Staple Food Meat, fish Other Clothes Social relation (e.g wedding ceremony, festival…) House maintenance and furniture Tourism Wedding ceremony celebration Total expenditure 2014 Reason 0= too young Temporary leave = financial reasons 2= physical reasons (illness/ injury) 3= Need child for other activities 4= others, specify Quit/stop 11= financial reasons 12= physical reasons 13= need child for other activities 14= school was too far 15= children was not interested in education 16= parents were nor interested in education 17 = other, specify Annual expenditure (VND) APPENDIX B: Tobit results for determinants of household engagement in forest activities Table 9: Tobit results for determinants of household forestland holding in 2014 Crland Hhmale Hhage Hhedu Lbrage Lnins Flmfrs frland n = 299 9.47*** (1.91) 1.55* (0.91) 0.05* (0.02) -0.23** (0.08) 0.55** (0.25) frland n = 299 9.85*** (1.91) 1.52* (0.90) 0.04* (0.02) -0.23*** (0.08) 0.49* (0.26) 0.00* (0.00) 0.00** (0.00) Logsumexp Dtb2014 frland n = 299 9.52*** (1.92) 1.41 (0.90) 0.04* (0.02) -0.24*** (0.08) 0.41 (0.26) 0.00* (0.00) 0.00** (0.00) 0.40 (0.29) frland n = 299 9.47*** (1.92) 1.39 (0.90) 0.04* (0.02) -0.24*** (0.08) 0.41 (0.26) 0.00* (0.00) 0.00** (0.00) 0.38 (0.29) 0.38 (0.50) frland n = 299 9.74*** (1.93) 1.48 (0.91) 0.04* (0.02) -0.23*** (0.08) 0.48* (0.27) 0.00* (0.00) 0.00** (0.00) 0.38 (0.50) Num_mbk 0.03 (0.33) Constant -0.53 -0.94 -1.67 -1.65 -0.96 (1.56) (1.55) (1.63) (1.63) (1.55) chi 64.98 73.64 75.57 76.14 74.41 prob > chi2 0.0000 0.0000 0.0000 0.0000 0.0000 * means significant at 10% level; ** means significant at 5% level; *** means significant at 10% level household is dropped because of its influential impact on the coefficients of fmlfrs, and households are dropped due to missing data on either logsumexp Table 10: Tobit results for determinants of household plantation area 2014 Crland Hhmale Hhage Hhedu Lbrage Lnins Flmfrs plt n = 299 4.03*** (0.95) 0.79* (0.45) 0.03** (0.02) -0.03 (0.04) 0.41** (0.13) plt n = 299 4.12*** (0.95) 0.79* (0.45) 0.03** (0.01) -0.02 (0.03) 0.39*** (0.13) 0.00 (0.00) 0.00* (0.00) Logsumexp Dtb2014 plt n = 299 4.10*** (0.96) 0.78* (0.45) 0.03** (0.01) -0.03 (0.04) 0.39*** (0.13) 0.00 (0.00) 0.00* (0.00) 0.03 (0.15) plt n = 299 4.01*** (0.95) 0.75* (0.45) 0.02** (0.01) -0.03 (0.04) 0.39*** (0.13) 0.00 (0.00) 0.00** (0.00) -0.00 (0.14) 0.61** (0.25) plt n = 299 4.13*** (0.96) 0.80* (0.45) 0.02** (0.01) -0.02 (0.04) 0.43*** (0.14) 0.00 (0.00) 0.00** (0.00) 0.62** (0.25) Num_mbk -0.12 (0.16) Constant -1.36* -1.51* -1.56 -1.53* -1.54 (0.78) (0.77) (0.82) (0.81) (0.77) chi2 58.63 63.02 63.06 69.21 69.77 prob > chi 0.0000 0.0000 0.0000 0.0000 0.0000 * means significant at 10% level; ** means significant at 5% level; *** means significant at 10% level household is dropped because of its influential impact on the coefficients of fmlfrs, and households are dropped due to missing data on either logsumexp Table 11: Tobit results for determinants of household absolute forest cash income in 2014 Crland Hhmale Hhage Hhedu Lbrage frinc n = 299 754.37 (555.70) 245.64 (259.55) -19.66*** (7.00) -46.80** (22.92) 71.93 (71.99) frinc n = 299 817.19 (560.55) 253.23 (259.63) -19.51*** (6.99) -47.91** (22.91) 60.48 (73.36) 0.02 (0.05) -0.15 (0.18) 975.63*** (140.13) 965.16*** (140.32) Lnins Flmfrs Logsumexp Dtb2014 frinc n = 299 777.67 (563.73) 239.89 (260.14) -19.37*** (6.97) -49.70** (23.10) 51.90 (74.96) 0.02 (0.05) -0.17 (0.19) 44.41 (85.02) 956.25*** (140.95) frinc n = 299 770.53 (567.69) 234.08 (262.24) -19.33*** (6.99) -48.85** (22.97) 46.90 (78.33) 0.02 (0.05) -0.15 (0.18) 963.01*** (140.20) Num_mbk 46.72 (95.31) Constant 669.31 668.02 584.26 -1.53* (447.94) (450.03) (476.26) (0.81) chi 57.27 58.31 58.58 69.21 prob > chi2 0.0000 0.0000 0.0000 0.0000 * means significant at 10% level; ** means significant at 5% level; *** means significant at 10% level household is dropped because of its influential impact on the coefficients of fmlfrs, and households are dropped due to missing data on either logsumexp Table 12: Tobit results for determinants of household relative forest cash income in 2014 Crland Hhmale Hhage Hhedu Lbrage rfrinc n = 299 6.28 (14.67) 7.55 (6.75) -0.68*** (0.18) -1.80** (0.60) -2.45 (1.90) rfrinc n = 299 7.27 (14.80) 7.67 (6.76) -0.67*** (0.18) -1.82*** (0.61) -2.63 (1.93) 0.00 (0.00) -0.00 (0.00) 26.71*** (3.70) 26.52*** (3.71) Lnins Flmfrs Logsumexp Dtb2014 rfrinc n = 299 11.29 (14.95) 9.00 (6.78) -0.69*** (0.18) -1.64*** (0.61) -1.73 (1.98) 0.00 (0.00) -0.00 (0.00) -4.68** (2.26) 27.39*** (3.72) rfrinc n = 299 11.20 (14.96) 9.32 (6.80) -0.69*** (0.18) -1.73*** (0.61) -1.45 (2.06) 0.00 (0.00) -0.00 (0.00) 26.66*** (3.69) Num_mbk -4.05 (2.51) Constant 48.10*** 48.18*** 57.24*** 57.24*** (11.74) (11.81) (12.62) (12.62) chi 68.37 68.84 73.16 73.16 prob > chi2 0.0000 0.0000 0.0000 0.0000 * means significant at 10% level; ** means significant at 5% level; *** means significant at 10% level household is dropped because of its influential impact on the coefficients of fmlfrs, and households are dropped due to missing data on either logsumexp APPENDIX C: Abstract of the presentation in the 25th annual meeting of Japan Association for Landscape Ecological in 6th, July, 2015 in Kitakyushu, Japan Forest Dependency in Northeastern Mountainous Villages, Vietnam Duc Anh TRAN*, Nobukazu NAKAGOSHI and Xuan Dang TRAN Graduate School for International Development and Cooperation, Hiroshima University, Higashi-Hiroshima, Japan, 739-8529 *Email: ductran.inno@gmail.com Forest dependency has been being widely documented for the sake of a sustainable development policy based on forest resources Various empirical evidences indicated that forests are important to rural livelihoods in developing countries (Rayamajhi et al., 2012) In Vietnam, a number of forest-oriented strategies for poverty reduction have been promulgated by the government (Sunderlin & Ba, 2005) Bac Kan province, located in the northeastern upland, is one chosen region for the implementation of these policies The local dominated geographical characteristic is high mountain ranges, with forest cover being 95.3% (BPI, 2012) However, as many other provinces, while the participation of many types of forest resource into the local livelihoods remains ambiguous, poor indigenous people are incessantly converting forests into agricultural lands to mitigate their food shortage (Sunderlin & Ba, 2005) Consequently, the promotion of forest-related business faces immense challenges This research is aimed at evaluating the forest dependency of rural households at two villages in Bac Kan, which expectedly enhance the local forest management and development policies To be more specific, in the first place, the economic share of forest income in total household income is comprehensively calculated Second, the impacts of several household characteristics are quantitatively analyzed, shedding light on the determinants of households’ forests reliance With a view of achieving those objectives, several methodologies are utilized Primarily, a survey with sound structured questionnaires will be conducted to obtain detailed information on household attributes and income sources Equally important, interviews with local representatives will be carried out to get insight into the regional context Finally, data analyses are descriptive statistics and a multiple regression model, resulting in concrete statistical testimony to the household forest dependency References BPI.(2012) Bac Kan Province Portal Information http://backan.gov.vn/Pages/tim-hieu-bac-kan-129/dieukien-tu-nhien-139/C490iE1BB81u20kiE1-1206ca3a0ad684b.aspx Rayamajhi, S., Smith-Hall C & Helles, F.(2012) Empirical evidence of the economic importance of the Central Himalaya forests to rural households Forest Policy and Economics, 20: 25 – 35 Sunderlin, W.D & Ba, H.T.(2005) Poverty Alleviation and Forests in Vietnam Center for International Forestry Research (CIFOR), Jakarta ... the economic contribution of products from household managed forests to rural livelihoods in mountainous villages of Vietnam Objective 2: To identify determinants of household’s engagement in forest. .. on forest activities in such setting remain limited This study captures the economic contribution of forest products to household income in the context of household managed forests by analyzing... surveys allow investigation in the contribution of each household income sources in According to PEN results, forest income accounts for about 22 percent of household total income Within this number,