• Journal of Korean Society of Forest Science
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• v.96 no.6
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• pp.705-713
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• 2007

The purpose of this study was to understand the organization and the forestry household income applied the result of 2005 Forestry Census and the Economic survey of Forest household in Korea. As a result of the analysis, there are 97,108 households of a forester in korea 2005. Full time forestry household occupied 7,925 families (8.2%), part time forestry household occupied 88,183 families (91.8%). Therefore, the most household of a forester is part time forestry household in korea. The average people of the household of a forester family is 2.7 people. The age of forest manager are sixties nearly, over sixty years old forest manager occupied 51,505 people (53%). The forest management period of forestry households is more than 6 months in 39,229 families (40.4%), less than 1 month in 7,216 families (7.4%). The average area of forestry households owning forest is 4.6ha. According to the type of business, logging families possesses 19.5 ha. The mean income of forestry households is \27,148,000. One of them, forestry income is \6,529,000, which occupied 24.1%. Furthermore, forestry households less than \5,000,000 forest product sales performance occupied 51,633 families, which is 64%. Forest operating costs is \6,566,000 mean per family. In addition, the number of a forestry household resident villages is 11,829 villages, where is 32.8% of whole villages in korea. There are 2,979 villages where reside forestry household in gyeongsangbuk-do.

• Journal of Korean Society of Forest Science
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• v.106 no.4
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• pp.497-508
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• 2017

This study conducted to examine about the income inequality and bi-polarization for forestry household. For this purpose, Gini coefficient and Atkinson index were used to analyze the income inequality for forestry household. Also, DER index were employed to show their income bi-polarization. Before using these methodologies, forestry household income was divided into three parts that was forestry income, non forestry business income and transfer income. And then, income inequality and bi-polarization were analyzed respectively. The result shows that forestry household income inequality was higher than whole household inequality. Apart from transfer income, forestry household income, forestry income and non forestry business income inequality was aggravated. At the same time, these tendency was able to observe the bi-polarization for forestry household income and other income sources.

• Journal of Forest and Environmental Science
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• v.33 no.4
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• pp.355-360
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• 2017

This study was aimed to analyze the increased forestry incomes by combining timber production and wood processing, which is one of 6th industrialization types in Korean forestry. The selected household has been engaged in forestry for two generations and they produce timber and associated wood products in their own facility. The wood products include dimension lumber, interior wood material, cutting board, and cube chips, the household also utilize logging and sawmill residues as well as seed and seedlings as by-products. Incomes and expenses that have been incurred on individual processes of the sequential timber production and wood processing were surveyed, and we analyzed the economic outcomes of entire business. The results of this study indicate that the gross income of the household is 122.3 million Korean won and the net income is 93.6 million Korean won. The net income of the household is approximately 2.8 times higher than the average net income of whole households in the forestry of Korea in 2016, which is approximately 4.3 times higher than that of households that have been particularly engaged in timber production over the country. We found that the 6th industrialization by combining the two sequential processes creates approximately 3.2 times as much added value compared to the case relying on timber production only.

• Journal of Korean Society of Forest Science
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• v.108 no.3
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• pp.392-404
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• 2019

The purpose of this study was to identify the impact of various income sources on income inequality of forestry households. Data from the Forestry Household Economy Survey from 2013-2016 were analyzed using the Gini coefficient decomposition method via income source. In particular, the income inequality analysis of forestry households was broken down into separate analyses based on group, i.e., the whole of forestry households and the five income quintile classes. The results of the analyses showed that income inequality of forestry households is primarily affected by forestry and nonforestry incomes and income quintile class. Moreover, income inequality of the highest income quintile class was largely affected by forestry income compared with other sources of income, whereas that of other income quintile classes was largely affected by nonforestry income. Therefore, in order to reduce income inequality in forestry households, it is necessary to increase the proportion of forestry income in the lower four quintile classes. Given that the income of the lowest quintile class is negative, it is necessary to devise ways to improve the proportion and quantity of forestry income. At the same time, as forestry income increases, a policy alternative is also required to improve inequality in forestry income.

• Journal of Korean Society of Forest Science
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• v.97 no.1
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• pp.77-82
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• 2008

For the last few decades, forest resources in Korea have continuously increased in terms of their stocks. However, due to the low profitability of timber harvesting in Korea, their economic values have not been well recognized. Furthermore, their economic values have not been counted in national statistics associated with forest resources such as the Forestry Household Economy Survey or the National Accounting. This research fundamentally aimed at building a forest valuation system or a procedure that enables one to evaluate the national-level economic values of timber assets in Korea. For this research, it is necessarily required to understand the principles of appraisal methods and any issues raised in their practical applications. Thus, a comprehensive review of appraisal methods utilized in Korea and other countries was conducted in this research. Also, the current valuation system of the National Forests in Korea was investigated. Through the review and the investigation, it was found that an alternative consists of two appraisal methods, the 'Capitalized Income Value' method adopting the Internal Rate of Return (IRR) for the below-rotation age forest and the 'Derived Residual Value' method for the above-rotation age forest, could be the most acceptable for evaluating timber assets of forestry households derived from the Forestry Household Economy Survey in Korea.

• Journal of Korean Society of Forest Science
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• v.97 no.3
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• pp.274-284
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• 2008

For forest valuation, various input data were generally required: for example, slope, timber stocks, logging costs, hauling costs, market values of timber, afforestation costs, thinning costs, and so on. To enhance the efficiency of forest valuation process, it would be helpful to guide how and where to acquire such data sets. Moreover, to make an appraisal of timber assets through the Forestry Household Economy Survey, it would be inevitable to use standardized input data by region or tree species. Therefore, this research intended to develop a methodology of standardizing each input data, and to present its available data sources. Also, a guidance was presented to explain how to control input data within the appraisal process. Then, the appraisal process were analyzed and summarized in four types of information such as system flowchart, process flowcharts, detail flowcharts, and skimmer data, which are essential elements in developing an appraisal software, named EnVAST (Engine of Valuation System for Timber Assets). The software was designed to generate 'the standard forest valuation table' by species and province as the final output that is applicable for the forest valuation through the Forestry Household Economy Survey in Korea.

• The Korean Journal of Applied Statistics
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• v.11 no.1
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• pp.29-39
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• 1998

The Farm Household Economy Survey (FHES) is carried out by the Ministry of Agriculture and Forestry every year. In this paper, we reveiwed the current status of the FHES and assessed the precision of the survey results. Finally we proposed some recommendations for improving the precision and presented the improvable directions of FHES with some feasible solutions.

• Journal of Forest and Environmental Science
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• v.26 no.1
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• pp.9-15
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• 2010

This paper analyzes data on the plant species diversity and their contribution to the livelihoods of rural people in five villages of Domar upazila, Nilphamari district, Bangladesh. Assessment was done by means of multistage random sampling. Information collected from a total of 40 households ranging from small, medium and large categories. A total of 52 plant species belonging to 34 families were identified as being important to local livelihoods. Fruits (37%), timber (23%) and medicinal (17%) species were the most important plant use categories. Determination of the relative density of the different species revealed that Areca catechu constitutes 19.17% of homestead vegetation of the area followed by Artocarpus heterophyllus, which occupies 10.34%. Margalef index showed that there is no major difference (5.11 for large, 5.49 for medium, 4.73 for small) across the different size classes and Shannon-Weiner Index of the study area varies from 2.75 to 2.98. Results show that the average annual homestead income varied from US$108.69 to US$291.67 and contribute 6.63% of the household income.

• Forest Science and Technology
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• v.14 no.4
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• pp.192-203
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• 2018

This study analyzed the distribution of forest income and other variable sources of rural household income and considered their importance for the reduction of income inequality and poverty. We employed Gini decomposition to measure the contribution of forest income and other sources of income to income equality and assess whether they were inequality-increasing or inequality-decreasing in the 14 villages. The forest income Gini correlation with total income was very high, $R_k=0.6960$, and the forest income share of total rural household income was 35% ($S_k=0.3570$). If the income earned from forest activities was removed, the Gini index would increase by 10.3%. Thus, if people could not access forest resources because of vast deforestation, perhaps from the limitations of government-managed forestry, unplanned clearing of forest land for agriculture or the granting of ELCs, there would be an increase in income inequality and poverty among rural households. The findings suggest that policy makers should look beyond agriculture for rural development, as forest resources provide meaningful subsistence income and perhaps contribute to both preventing and reducing poverty and inequality in rural communities. The study found that non-farm activities were inequality-increasing sources of income. The share of non-farm income to the total rural household income was $S_k=0.1290$ and the Gini index of non-farm income was very high, $G_k=0.8780$, compared with forest and farm income. This disagrees with other studies which have reported that non-farm income was inequality-decreasing for the rural poor.

• Journal of Korean Society of Forest Science
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• v.109 no.1
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• pp.99-108
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• 2020

Although the relationship between income and income inequality has previously been discussed, the present study applies a dynamic approach to analyze the specific relationship between forest household income and income inequality. For this analysis, a unit root test and a cointegration test were conducted to characterize the nature of income time-series data. After converting unstable time-series data into stable time-series data, a VAR model was estimated. Based on this model, an impulse-response was generated and variance-decomposition analysis was performed. These analyses showed that the effect of forest household income was relatively larger than that of the Gini coefficient, and that the impact of forest household income not only caused income to increase but also caused the Gini coefficient to decrease. In addition, the impact of the Gini coefficient had an impact on reducing forest household income and further increasing income inequality. We conclude that, with the aim of alleviating the inequality of forest household income, an income growth policy would be more effective than an income distribution policy.