• Journal of Fisheries and Marine Sciences Education
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• v.15 no.2
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• pp.166-175
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• 2003

In order to offer fundamental data for the standard of comfilation of the budget on the compensation money for the reduction of fishing baot and index of investigation for computation on the average earnings of reduction of fishing boat, the fluctuation of actual outputs, expenses, earnings and the difference by type of coastal and off-shore fishery was investigated and analyzed. The results are as follows : 1. The average ouput money by large powered purse seine fishery was much with about 3,510 million won, but the average output money by off-shore gill nets fishery was little with about 8.4 million won. 2. The average catch by large powered purse seine fishery was many with about 296,000 M/T, but the average catch by eastern sea danish seine fishery was few with 4,600 M/T. 3. The average expense by large powered purse seine fishery was much with about 3,360 million won, but the average expense by diving fishery was little with 6.3 million won. 4. The average earning by large powered purse seine fishery was much with about 240million won, the average earning by offshore long line fishery was little with 18 million won. 5. The average earning rate by diving fishery was much with 31.62%, but the average earning rate by large powered purse seine fishery was little with 7.30%.

• Journal of Animal Science and Technology
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• v.53 no.4
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• pp.319-324
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• 2011

This study was conducted to analyze demerits of the sire evaluation system using annual earnings and to examine relationship between annual earnings and finish time in home-produced thoroughbred racehorses. The average number of progenies and number of starts per sire were 34 heads and 221 times, respectively. On the other hand, the number of progenies with the average age of 2 years and the number of starts were 9 heads and 25 times, respectively. The earnings of the horses with the age of 2 years accounted for 8.3% of annual earnings. The simple correlation coefficient between the number of progenies and the number of starts in annual earnings were 0.922 and 0.934, respectively. The correlation coefficient between the number of progenies and the number of starts was very high (0.985). The number of progenies and starts of sires for the first year of test career were very low (6 heads and 17 times), and there was very close relationship between number of progenies and annual earnings by the year of test career. The number of progenies was over 40 heads during the first 4 years of test career, and as the number of progenies increased the average earning index increased. The average earning index of sires with less than 30 progenies was lower than 1.00. When the number of progenies was less than 10, the average earning index was in the range of 0.06~0.13, indicating that the number of progenies affects much for determining the ranking of sires. The correlation coefficient between breeding value for finish time and annual earnings per start was very high (-0.524~-0.633) compared with other traits.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.571-579
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• 2020

This paper examines how human capital and other economic variables, such as private investment, economic growth, government investment, inflation, and unemployment influence inequality in Indonesia's provinces. We apply panel data model with fixed effect estimation for the data of 34 provinces from the period 2013 to 2019. We develop a new index for human capital using the education index approach. The results show that human capital has a negative and significant effect on income inequality. An increase in human capital is related to an increase in knowledge and competence due to the longer average school year and expectations of the school year. Human capital has increased the possibility of a person being accepted into the job market and earning a higher income; hence, it lowers income inequality. We also find that inflation leads to a higher gap of income distribution. A further implication of this situation is that the rise in inflation causes an increase in low-income people, and as a consequence, makes their lives worse off. This paper will be beneficial for policy-makers for whom human capital, which is measured using an education index, is an important factor that significantly affects income inequality, in addition to other economic factors.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.221-229
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• 2017

In the international businesses human resource elements acquired in different countries might have different values in varied industries due to the different quality of education and experiences in the original countries. Using selection models to evaluate expected values in earnings equation of human resource elements such as education and experiences etc. acquired in sending countries, system equations are expanded to examine also the values of science and engineering degrees in technology jobs with selectivity bias correction. This paper used the US census survey data of 2015 on earnings, academic degrees, occupations etc. The US has long maintained the policy of accepting more STEM workers than any other countries and helped maintaining own technological leadership. Assuming per capita GDP gap between the sending country and the US downgrades immigrant human resource quality, it rarely affects occupational selection but depresses earnings on average by two or more years' worth of education. Immigrant quality index in the sense of GDP gap appears to be a valid tool to assess the expected earnings of the worker with. Engineering degrees increase significantly the probability of selecting not only engineering jobs but also general management jobs, as well as increasing the expected earning additionally over nine years'worth of education. Getting a technology job is additionally worth about four years of education. Economics and business degrees are worth additionally almost six years of education but humanities degrees depress expected earnings. Since years after immigration does not very fast enhance earnings capacity, education level and English language ability might be more useful criteria to expect better future earnings by.