• Journal of Korean Society of Forest Science
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• v.98 no.5
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• pp.548-557
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• 2009

For centuries, forests have been a key component of rural livelihood. They are important both socially and economically in Nepal. Firewood and fodder are the basic forest products that are extracted daily or weekly basis in most of the rural areas in Nepal. In this study, a field survey of 100 households was conducted to examine the degree of forest dependency and forest resource availability, households' livelihood strategy and their relationship with forest dependency in Chitwan, Nepal. A household' response indexes were constructed, Gini coefficient, Head Count Poverty Index (HCI) and Poverty Gap Index (PGI) were calculated and one way ANOVA test was also performed for data analysis. Data revealed that 82/81% of all households were constantly used forest for firewood and fodder collection respectively while 42% of households were used forest or forest fringe for grazing. The Forest Product Availability Indexes (FPAI) showed a sharp decline of forest resources from 0.781 to 0.308 for a 20-yr time horizon while timber wood was noticeably lowered than the other products. Yet, about 33% of households were below the poverty threshold line with 0.0945 PGI. Income distribution among the household showed a lower Gini coefficient 0.25 than 0.37 of landholdings size. However, mean income was significantly varies with F-statistics=246.348 at P=0.05 between income groups (rich, medium and poor). The extraction of firewood, fodder and other forest products were significantly different between the income group with F-statistics=16.480, 19.930, 29.956 at P=0.05 respectively. Similarly, landholdings size and education were also significantly different between the income groups with F-statistics=4.333, 5.981 at P=0.05 respectively. These findings suggested that income status of households was the major indicator of forest dependency while poor and medium groups were highly dependent on the forests for firewood, fodder and other products. Forest dependency still remains high and the availability of forest products that can be extracted from the remaining forestlands is decreasing. The high dependency of households on forest coupled with other socioeconomic attributes like education, poverty, small landholders and so on were possibly caused the forest degradation in Chitwan.Therefore, policy must be directed towards the poor livelihood supporting agenda that may enhance the financial conditions of rural households while it could reduce the degree of forest dependency inspired with other income generating activities in due course.

• East Asian Journal of Business Economics (EAJBE)
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• v.8 no.1
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• pp.57-69
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• 2020

Purpose - This study examines what are the asset market fluctuations in Europe and how each economic variable affects major variables, and explore the dynamics of housing and stock market through Greece. The variables under consideration are balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), M3, real rate of interest (IR_REAL) and household credits (LOAN). We investigate the functional and causal relationships between housing and stock market. Research design, data, and methodology - Vector error correction model (VECM) is used to figure out the dynamic relationships among variables. This study also contains the augmented Dickey-Fuller unit root, cointegration, Granger causality test, and impulse response function and variance decomposition analysis by EViews 11.0. Results - The statistical tests show that all variables under consideration have one unit root and there is a longterm equilibrium relationship among variables for Greece. GDP, IR_REAL, M3, STOCK and LOAN can be considered as causal factors to affect real estate market, while GDP, LOAN, M3, BCA and HOUSING can bring direct effects to stock market in Greece. Conclusions - It can be judged that the policy that affects the lending policy of financial institutions may be more effective than the indirect variable such as monetary interest rate.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.17 no.1
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• pp.64-80
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• 1991

The SKINTEX Method is based on a two-compartment physico-chemical model which includes a Biomembrane Barrier in compartment one and an organized macromolecular matrix in compartment two. Test samples absorb onto or permeate through the keratin/collagen Biomembrane Barrier and then can interact with the organized macromolecular matrix. Changes in the integrity of the barrier release a dye indicator: Changes in the matrix can alter its transparency. The sum of these two responses is read spectrophotometrically at 470nm. An early investigation of 950 chemicals and formulations in the SKINTEX System produced results which were 89% concordance to in vivo Draize dermal irritation results obtained with 24-hour occluded application of test samples with-out abrasion and standard scoring. Alkaline materials were analyzed in a specialized SKINTEX AMA Protocol. In this early study, the model did not distinguish nonirritant test materials and formulation with PDII(Primary Dermal Irritation Index)in the range from 0 to 1.2, A High Sensitivity Assay Protocol(HSA)was developed to amplify the changes in both compartments of this model and provide more accurate calibration of these changes. A study of 60 low irritation test samples including cosmetics, household products, chemicals and petro-chemicals distinguished nonirritants with PDII $\leq$ 0.7 for 26 of 30 nonirritants. A second protocol was developed to evaluate the SKINTEX model predictability with respect to human irritation. The Human Response Assay (HRA )has been optimized based on differences in penetration and irritation responses in humans and rabbits. An additional 32 test materials with different mechanisms and degrees of dermal toxicity were evaluated by the HRA. These in vitro results were 86% concordant to human patch test results. In order to further evaluate this model, a Standard Chemical Labelling (SCL) Protocol was developed to optimize this system to predict Draize dermal irritation results after a 4-hour application of the test material. In a study of 52 chemicals including acids, bases, solvents, salts, surfactants and preservatives, the SCL results demonstrated 85% concordance to Draize results for a 4-hour application of test samples on non-abraded rabbit skin. The SKINTEX System, including three specialized protocols, provided results which demonstrated good correlation to the endpoint of dermal irritation in man and rabbits at different application times.

• The Journal of Industrial Distribution & Business
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• v.9 no.5
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• pp.63-72
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• 2018

Purpose - This work analyzes, in detail, the specification of vector error correction model (VECM) and thus examines the relationships and impact among seven economic variables for USA - balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), a measure of the money supply that includes total currency as well as large time deposits, institutional money market funds, short-term repurchase agreements and other larger liquid assets (M3), real rate of interest (IR_REAL) and household credits (LOAN). In particular, we search for the main explanatory variables that have an effect on stock and real estate market, respectively and investigate the causal and dynamic associations between them. Research design, data, and methodology - We perform the time series vector error correction model to infer the dynamic relationships among seven variables above. This work employs the conventional augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root techniques to test for stationarity among seven variables under consideration, and Johansen cointegration test to specify the order or the number of cointegration relationship. Granger causality test is exploited to inspect for causal relationship and, at the same time, impulse response function and variance decomposition analysis are checked for both short-run and long-run association among the seven variables by EViews 9.0. The underlying model was analyzed by using 108 realizations from Q1 1990 to Q4 2016 for USA. Results - The results show that all the seven variables for USA have one unit root and they are cointegrated with at most five and three cointegrating equation for USA. The vector error correction model expresses a long-run relationship among variables. Both IR_REAL and M3 may influence real estate market, and GDP does stock market in USA. On the other hand, GDP, IR_REAL, M3, STOCK and LOAN may be considered as causal factors to affect real estate market. Conclusions - The findings indicate that both stock market and real estate market can be modelled as vector error correction specification for USA. In addition, we can detect causal relationships among variables and compare dynamic differences between countries in terms of stock market and real estate market.