The Impacts of Forest Plantation on Household’s Income

This study uses differences in differences (DID) method combined with OLS regression to assess the impact of forest plantations on household income and livelihoods in rural areas of Bac Kan Province in Vietnam based on the 2017 household living standard field survey data and VRAFC 2011 database. Results indicated that forest plantations have no impact on improving the household’s income. This is explained by income from forest plantation that is uneven among households in 2017 and household’s income survey data that is often inaccurate because the prolongation of the production cycle in planted forest activities and error in income calculate. On the other hand, the study also found the impact of households gender, off-farm employment, household size, a land area owned, land security and rural credit on incomes and expenditure of households in the study area. We recommend that some policies such as land tenure reform, diversification economic activities and rural employment, to enhance the ability to access resources and improve capacity participation in non-farm activities should be proposed to help improve households living standards in rural areas of Bac Kan Province in particular and Vietnam in general.


Introduction
As the world becomes more and more interested in addressing climate change issues, the effect and impact of deforestation and forest degradation on climate are also getting more and more focused. This issue helps confirm the important role of the forest as a green lung of humankind, helping to regulate the climate and sustain life on earth. On the other hand, forests also play a large role in poverty reduction and livelihood improvement of people around the world, which is reflected in reports and articles published worldwide, e.g. improve livelihoods, generate income and employment, provide safety networks to minimize risks, provide firewood for farmers or it has a role as a savings mechanism and cash allowance [1] [2] [3] [4].
Furthermore, studies in the world evaluating the impact of forest plantations on household income have majority focused on commercial forests plantation developed by enterprises. These studies have shown that the forest plantations have potential benefits from increasing forestry income, improving infrastructure, diversification of income sources and creating jobs [5] [6] [7] [8] [9]. On the other hand, these studies also indicated that poverty levels become more serious in areas where commercial plantation forests had expanded [4] [10]- [15].
Only a few studies have evaluated the contribution forest plantations to rural livelihoods of farm households in the world [16] [17] [18] [19].
The forestry sector is considered to play an important role in economic development in Bac Kan province. In recent years, along with innovations in management, scientific research activities in the forestry sector and development of forest planting techniques have also received more attention. Forest planting programs and projects are implemented on a provincial scale with many production plantation models established, many technical measures have been developed into processes, thence help improve and enhance the efficiency of afforestation activities [20].
In addition, to our knowledge, there is no empirical evidence on whether or not a participation in plantation improves the income of the participant farm households; no specific research has been done to assess the impact forest plantation to improve farm household's income in the rural area of Vietnam. Most of the research has been done in relation to plantation development focusing on the economic efficiency of a particular crop, the development of the wood processing industry, and the policy for payment for forest environmental services (PES) and forest land allocation policies [21]- [26]. Hence, this study attempts to provide empirical evidence on the impact of forest plantations on household cash income in the study areas.
In order to assessing the impact of forest plantations to farm household income in Bac Kan province of Vietnam, this study will: 1) evaluate the factors affect to household's income in study area; 2) evaluate the impact of smallholder plantation on economic benefits (total cash income and use of improved agricultural input) of the forest planting participant farm households in study area. Thence, the study will provide policymakers with the necessary data for policy adjustment and proposes the solutions help to improve income and rural livelihoods of households in the context of each specific area in the future.

The Study Area
Bac Kan province is located on the North East extension of Vietnam (22˚N -23˚N, 105˚E -106˚E) ( Figure 1). The province with population of 308,300 and 81.24% of the population living in a rural area, and composed predominantly of ethnic minorities, including Tay, Nung, Kinh, Dao, Mong, Hoa, San Chay, and others [27]. With a land area of 4859 km 2 , Bac Kan is the smallest province in the north of Vietnam and has a relatively low population density compared to the provincial average (63 person per km 2 compared to 314 person per km 2 ). The climate is subtropical monsoonal with hot wet in the summers and cool, dry in the winters.

Data Collection
We adopted a combination of secondary data and field survey data collection in this study. Primary data were collected covering the period from June to August

The Analytical Model
To modeling the participation of farmers in afforestation activities and impact of forest plantations on income of farm households, the study followed researches of [15] [17] [28] [29]. The difference-in-difference model to explain the variation on income of farm household's base on the impact of forest plantation written in the formula: (2) In which   (2) represents the impact of forest plantation on farm household's income by sampled households with incorporating thirteen variables (shown in Table 1). It is representing household, policy/institution factors, the difference in time of the field surveys, forest plantation decision and interaction between these two variables.   In order to determine the appropriate model, the paper will conduct implement according to the steps: Step one, regression the basic model (using explanatory variables: PLANT, T and T*PLANT) to determine if there is no impact of other factors, forest plantation has an impact on income of farm households in rural areas in overtime or not.
Step two, implement develop an extended model (with the effect of other factors beyond the forest plantation) using the method "top-down approach", from general to simple. Specifically: Firstly: Based on the theoretical framework and previous studies, by linear regression model with all the relevant variables shown above, the paper gives an initial general model.
Secondly: Evaluate the suitability of the model based on adjusted P-value, R 2 and R 2 Adjusted; remove variables that are insignificant statistically out of the model and select the "best" model.
Thirdly: Check and overcome errors in linear regression models such as multicollinearity phenomenon, Heteroskedasticity phenomenon.
In conclusion, the combination between OLS regression method and DID methods will show that whether forest plantation has a positive impact on the income of rural households in Bac Kan, and how is the level of these impacts (show by the value of T*PLANT variable). Thence, propose certain interventions to improve the living standard for farm households in rural area of Vietnam.

Descriptive Statistics and Examine Statistic Significantly
The field survey results show that, in 2011, two groups of households have similar characteristics such as age, education of household head, off-farm work, characteristics of household, demographic characteristics, per capita income, per capita expenditure of household, etc. However, there are some different characteristics between these two groups of households such as gender, occupations of the household heads, loan of households etc. Therefore, in order to conclude whether there is really a difference between the two groups, we are necessary to perform a T-test on the average difference between the two groups of households (see Table 2

Analyzing the Impacts of Forest Plantation on Household's Income
In order to assess whether forest plantation helps to improve the household's li-    has an impact on the average per capita income of the households.
Gender of households head (GENDER) has negative and significant effect on incomes generated from farm households. Female-headed households on average earn 1.921 million VND higher incomes than male-headed households. The lower expected earnings with male-headed households may be proved because the lower probability of becoming involved in the off-farm work activities (worker in factories) than households who have female-headed households. This effect is significant at the 10% level. This result supported by finding from Nigeria by Yakubu et al. [30]; but opposite with finding from Myanmar of Nem Nei Lhing et al. [31], from Vietnam by Loan and Huong [32].
Our study also shows that household size has a strong impact on the living standards of households in the study area. On the one hand, there was a negative correlation between farm household's income and the size of the household. As the size increased by one member, the profits were seen to reduce corresponding with regression coefficient on the regression model about 3.183 million VND. This situation can be explained that the increased in the family size will put higher pressure to earn more to money for members for cover their basic needs cause increase in expenditure for food, clothes, health and in some case is educate because a larger number of children may need to go to school, thence limited funds for total households expenditures and lead to farm households with more member will have lower per capita income than other farm households. This results opposite with finding from Yemen of Safa [33], from and from Bangladesh by Rahman [34] because these results indicate that large size of household will supply more productive in term of labor force and has better opportunities to diversify their income from farm and off-farm activities. However, it also supported by finding from Vietnam by Nghi and Trinh [35], from Zambia by Banda [36], and from Kenya by Wanjiku [37] because these studies agree that households who have large-scale may be able to only bring a high per capita income if the dependency ratio in the household is small. In contrary, large household size will lead to low per capita income if the dependency ratio in households is high.
Land is one of the important inputs of the production process, especially agricultural production. Through farm households field survey results in the study area, mainly agricultural and forestry farm households, the results have pointed out that land size is an important factor affecting the average income of farm households in study area. With significant at the 1% level which means that a one extra hectare increase of land size of farm households it resulted in an increase in per capita income about 3.385 million VND y −1 . This finding agrees with result from Yemen by Safa [33], from Myanmar of Nem Nei Lhing et al. [31], from Open Access Library Journal Bangladesh by Rahman [34] Vietnam by Loan and Huong [32] and Hai [26]. These researches indicate that an increase in land area is clearly one of the solutions to help farmers improve their incomes besides addition to improving their occupation, credit, and other factors.
Distance to the nearest the market center was found to have a statistically significant and negative effect on farm households income; or on the other word it indicated that the households who have far away distance from their home to the markets corresponding to the lower the per capita income. With every kilometer of increased distance from households home to the market, per capita income of farm households will decrease corresponding by 1.618 million VND. The reason might be, the closer of the farm household is to the market center, the more opportunities to engage in non-farm activities to generate income, in addition, this would make them minimizes the transportation costs to the market place when households buy and selling agricultural products on the market and leads to increased farm household incomes. This results also supported by finding from Sudan by Hassan [38], from Eritrea by Teame and Woldu [39], from Kenya by Wanjiku [37].
Respondents show that off-farm work variable (OFFWORK) has positively correlated with the total income per capita variable. It means that in the condition of other factors that are constant, those farm households who have incomes from off-farm work activities may have a higher per capita income approximately 4.902 million VND per person y −1 than those with only income from agriculture activities. This results also supported by finding from Eritrea by Teame and Woldu [39], from Kenya by Wanjiku [37] when these author assert that diversifying income generation activities will help farmers improve their living standards better than focusing on agricultural production only; because agricultural activities are often accompanied by unstable risks and income, with a large idle time.
If farm households could how to make use of this idle time to do other jobs such as working as hired labor, doing part-time job and business, they are likely improving their income.
The results from Table 3 also indicated that land ownership security also positive impact to farm household income in Bac Kan province at the 5% significance level. This means that households with land security are guaranteed seem to have a higher per capita income than the other group about 1.729 million VND y −1 . This similar to observed by Wanjiku [37], when the author implies that farm households income improved significantly in the case of farm households are assured property rights of land.
The finding also shows that access to credit had a positive correlation to average income which means that if the other factors are constant, those who participated to rural credit are likely had higher income than those who did not participant. The income for those who had participant to credit was found to higher by 3.223 million VND y −1 than those who did not participant. This may be explained that any activity to generate income needs to have a sufficiently large Open Access Library Journal amount of capital to make the activity continuous and uninterrupted [36] [39].
On the other hand, those households who borrow money from credit institutions to invest in production activities often have more work motivation to create more income to repay loans from banks; hence, they try to try to use their loans in the most effective way, avoiding waste [40]. This result was statistically significant at 99% confidence level.
Astonishingly, the impact of forest plantation on per capita income was found insignificant statistically in the models 2 and 3. This may be explained by the    With a 5% significance level, P-value (Prob) = 65.13% indicated that it is impossible to reject the hypothesis H 0 , or these variables such as AGE, EDU, EXTEN can be removed from the model.

Appendix 5. The Test of Relevance of the Regression Model on the Relationship between per Capita Income and Forest Plantations and Other Factors
Hypothesis H 0 : 1 2 3ˆˆˆ0 i β β β β The regression results shown that in three regression models on the relationship between per capita income and forest plantation and other factors, the value of Prob (F-statistic) = 0.000, it always less than 1%, this demonstrated that three models are statistically significant. In which, model 3 with adjusted R 2 is 52.6%, it approximately of model 2 and higher than adjusted R 2 of model 1, so model 3 is the most suitable model.