Sustainable assets and strategies for affecting the 2 income of forestry household : Empirical evidence 3 from South Korea 4

This study aims to identify the factors determining the income of forestry household in 14 South Korea. We examine an empirical analysis using 3-year panel data conducted by the Korea 15 Forest Service charged with maintaining South Korea's forest lands. The hypothesized factors 16 determining the income of forestry household are classified into four types of assets and three types 17 of livelihood strategies. We divided the income of forestry household (IFH) into three elements: 18 forestry income (FI), non-forestry income (NFI), and transfer income (TI). We assessed the influences 19 of household assets and livelihood strategies on each income. A random effect model was used as a 20 statistical analysis with valid 979 of forestry household for three years. We found that household 21 head's age, labor hours, savings, business category, cultivated land size, and region are significantly 22 associated with IFH. Also, FI is influenced by labor capacity, cultivated size, business category, 23 forestry business portfolio, and region while NFI is determined by household head's age, household 24 head's gender, forestry business portfolio, and savings. TI is affected by household head's age, 25 household head's education level, forestry business portfolios, savings, and region. The effect sizes 26 and directions vary across different types of income (IFH, FI, NFI, and TI). The findings show that 27 forestry in South Korea is highly dependent on sustainable assets and strategies. It is therefore 28 expected that the effectiveness of forest policies to increase the income of forestry household would 29 be differed by the source of each income. The results of this study draw attention to the need for an 30 income support policy that should consider the characteristics of household assets and livelihood 31 strategies in order to enhance IFH in South Korea. 32


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Forestry in South Korea is an industry based on the forest which covers 65% of the country's 37 land, playing significant roles in conserving biodiversity, maintaining the ecosystem, mitigating    As explanatory variables for financial capital, some studies used savings and loans at the same time [13,14,27,33], and others only loans [12,19]. Cash income, borrowing, access to loans [15,18], net 147 income [14], livestock value, non-farm business, and money lenders [27] were used. In this study, we 148 define financial capital as the immediate assets and liabilities corresponding respectively to savings 149 and loans.
size [14], area of cropland [29], and land claimed [13]. It is widely believed that the inputs required 152 for profit-maximization in the traditional forest production theory are land-based capitals. In studies 153 the production area of a specific product (  silviculture/logging, gathering, chestnut tree, astringent persimmon tree, nut tree, mushroom 163 cultivation, landscape material, and others. In many studies, forestry or agricultural product items or 164 business types are explicitly or implicitly defined as ways of sustaining a livelihood.

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The type of forestry in South Korea reflects the situation of forestry as many households 166 practicing forestry are often engaged in other businesses other than forestry. It is common that many livelihood strategy in this study. We further subdivide the part-time forestry business portfolio into 173 major part-time and minor part-time status by the proportion of forestry income relative to income 174 from other sources, specifically whether forestry income is more or less than other incomes.

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Geographical location can be considered either as a natural asset or a livelihood strategy, 176 depending on the household's motivation to reside in a particular region. We view the region as a 177 livelihood strategy because of a household's decision on the location of residence impacts on their 178 production and marketing strategy. For example, forestry income can be affected by varying local 179 conditions such as climatic factors, available resources, market characteristics, regional government 180 policies, and infrastructure. Zhu et al. (2017) mentioned that regional factors significantly influence 181 household investment behavior in NTFP business. Also, Kim and Lee (2014) reported that there is a 182 difference in the structure of agricultural income in each province. Therefore, accounting the 183 differences in specific regions and differentiating the structure of forestry by geographical and 184 administrative region can be considered as effective strategies.

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To sum up, the outcome of forest owner livelihood is generated and influenced by both the 186 household capitals and livelihood strategies. Therefore, we viewed household characteristics and livelihood strategies together as determinants of household income (Fig. 1).

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IFH can be divided into regular and irregular income. Irregular income is gained on an 197 occasional basis. In the regular income, there are forestry income (FI), non-forestry income (NFI), and 198 transfer income (TI) accounting 6.9 %, 1.7 %, and 8.1 % respectively (    246 247

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Based on equation (1), it is a static analysis if α = 0 while it is dynamic if α ≠ 0. If x is 250 correlated with η , uncontrolled heteroskedasticity may be in error and need to be controlled.

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In the processing of η , it can be classified into fixed effect and random effect using panel data.

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While the fixed effect is preferred when it needs to control completely η , the random effect is   Table 4.     The results of the random effects model are summarized in Table 8. Since the results of Breusch-

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Pagan LM are statistically significant, we can confirm that the use of the random effect model is 328 appropriate. Hausman test is also fulfilled, and its significant level is larger than 0.05, which also 329 supports the appropriateness of a random effect model.
As for FHI, we found that the household head engaged in the landscape tree growing industry 331 has a higher income than the household heads engaged in the silviculture/logging industry. Different income among household heads running different types of business have also been evidenced by

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This study attempts to investigate IFH and the quality of life in terms of sustainable livelihood 438 in rural villages rather than strengthening the competitiveness of forest products like an agricultural 439 field. We hope that the results of this study will provide necessary information about the structure of 440 forestry household income in South Korea and will help them make decisions that make their