Rural Migration and Changes of Agricultural Population (농민이촌(農民離村)과 농업인구(農業人口)의 변화(變化))
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- Korean Journal of Agricultural Science
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- v.1 no.1
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- pp.91-116
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- 1974
Taiwan agricultural development in the last decade has not been changed much since the accomplishment of land reform program. This is mainly due to the rapid development taken place within industry that agricultural development can not keep pace with. The increasing gap of rural-urban income discrepancy has caused socio-psychological unstability among rural people and inspire wants of out-migration. From 1961 to 1970, population of the ten largest cities showed an annual growth rate of 4.05%, while the population of the remainder of Taiwan showed 2.06%. Assuming the natural increase rate of these two population sections are similar, the difference of rural and urban annual growth rate can be at tributed to the flow of people from rural to urban sectors. The main objective of this paper is to identify the amount of agricultural out-migration and its impact on agricultural development and agricultural extension programs. Specifically, the objectives are to examine (1) rural-urban population composition (2) rural out-migration estimation (3) changes of agricultural population, and (4) implications for agricultural development and extension programs Some of the important findings are listed below; (1) The average agricultural out migration of the period 1960-1969 is estimated at around 60,000 per year. Take Tainan prefecture for example, the Male-Female Migration Ratio is 0.39 for age 20-24, 0.55 for age 25-29, 0.90 for 30-34. It is understood between age 20 and 34, the rural female migration rate is higher than the rural male. (2) Based on the population growth rate of 1950-1969, agricultural population is projected for the period of 1953 to 1989. By 1978, the agricultural population will reach its peak and begin to dedaine from 1980. The projected agricultural population in 1989 is 5,847,566 which occupies 29% of the Taiwan total population. (3) Assuming area of cultivated land keep unchanged as 905,263 ha. in 1970, and tif we can eliminate all 72% of part-time farms, then the average farm acreage for hose full-time farms will be increased to 3.6 hactares. This is unlikely to happen before 1989 without the government interference. (4) Less than 10% of adult farmer s of age 25-64 in 1969 enrolled in Farm Discussion Club, only 5% of adult farm women enrolled in Home Economics Club, and 5% of rural youth enrolled in 4-H Club. These statistics show a fact that only few farmers are reached by extension workers. Based on findings in this paper, some important suggestions are listed for future agricultural development. (1) Improve agricultural structure by decreasing agricultural population (a) Encourage farmers with less than 0.5 ha. of land to seek jobs outside of agriculture (b) Encourage joint cultivation and farm mechanization (c) Discourage rural migrants to Keep farm land (d) Provide occupational guidance program through extension education programs (2) Establish future farmers settlement project to assure rural youth have enough resources for farming. (3) An optimum Population policy should be integrated into rural socio-economic development and national development programs.
Recently, as the advent of the knowledge-based society, there are more people getting interested in the intellectual property. Especially, the ICT companies leading the high-tech industry are working hard to strive for systematic management of intellectual property. As we know, the patent information represents the intellectual capital of the company. Also now the quantitative analysis on the continuously accumulated patent information becomes possible. The analysis at various levels becomes also possible by utilizing the patent information, ranging from the patent level to the enterprise level, industrial level and country level. Through the patent information, we can identify the technology status and analyze the impact of the performance. We are also able to find out the flow of the knowledge through the network analysis. By that, we can not only identify the changes in technology, but also predict the direction of the future research. In the field using the network analysis there are two important analyses which utilize the patent citation information; citation indicator analysis utilizing the frequency of the citation and network analysis based on the citation relationships. Furthermore, this study analyzes whether there are any impacts between the size of the company and patent citation relationships. 74 S&P 500 registered companies that provide IT and communication services are selected for this study. In order to determine the relationship of patent citation between the companies, the patent citation in 2009 and 2010 is collected and sociomatrices which show the patent citation relationship between the companies are created. In addition, the companies' total assets are collected as an index of company size. The distance between companies is defined as the absolute value of the difference between the total assets. And simple differences are considered to be described as the hierarchy of the company. The QAP Correlation analysis and MR-QAP analysis is carried out by using the distance and hierarchy between companies, and also the sociomatrices that shows the patent citation in 2009 and 2010. Through the result of QAP Correlation analysis, the patent citation relationship between companies in the 2009's company's patent citation network and the 2010's company's patent citation network shows the highest correlation. In addition, positive correlation is shown in the patent citation relationships between companies and the distance between companies. This is because the patent citation relationship is increased when there is a difference of size between companies. Not only that, negative correlation is found through the analysis using the patent citation relationship between companies and the hierarchy between companies. Relatively it is indicated that there is a high evaluation about the patent of the higher tier companies influenced toward the lower tier companies. MR-QAP analysis is carried out as follow. The sociomatrix that is generated by using the year 2010 patent citation relationship is used as the dependent variable. Additionally the 2009's company's patent citation network and the distance and hierarchy networks between the companies are used as the independent variables. This study performed MR-QAP analysis to find the main factors influencing the patent citation relationship between the companies in 2010. The analysis results show that all independent variables have positively influenced the 2010's patent citation relationship between the companies. In particular, the 2009's patent citation relationship between the companies has the most significant impact on the 2010's, which means that there is consecutiveness regarding the patent citation relationships. Through the result of QAP correlation analysis and MR-QAP analysis, the patent citation relationship between companies is affected by the size of the companies. But the most significant impact is the patent citation relationships that had been done in the past. The reason why we need to maintain the patent citation relationship between companies is it might be important in the use of strategic aspect of the companies to look into relationships to share intellectual property between each other, also seen as an important auxiliary of the partner companies to cooperate with.
In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.
This paper studies the time-space and appreciation of the performance culture of Gwanseo region, which is considered to have formed a characteristic culture in late Joseon period. For this purpose, 4 gasa written in hangeul (Korean alphabet), as well as 4 yeonhaeng gasa, 108 articles of Gwanseoakbu were examined. Plus, among the 9 types of yeonhaengrok (Documents of Performance culture) written in Chinese character, those parts which describe the performance traits have been analyzed. Then, 'main list of terminology' has been deduced based on the categorization according to the following points : 1) subjects of performance and appreciation 2) time and period of performance 3) space of performance 4) contents of performance 5) background and motive for performance and 6) method of performance. Through this process, various 'nouns' and 'predicate verbs' in relation to performance culture emerged, which were systemized according to types of performance elements and categories. Major terminology includes predicate verbs and symbolic verbs such as nokuihongsang,' 'baekdaehongjang,' 'jeolsaekgeumga,' 'cheonga,' 'hwaryu,' 'gamuja,' and 'tongsoja,' as well as the terms already known such as gisaeng, iwon, yangbang, akgong, and jeonak, which refer to musicians and dancers. Subjects of performance were divided into performers and listeners, categorized into concert, music, and dance, according to performance form. In the case for music, it was divided into instrumental or vocal, solo or accompanied (byeongju, self-accompaniment). In the case for vocal music, noteworthy was the inclusion of profesional artist's singing (called gwangdae or uchang). The record of 23 names of popular artists from Gwanseo region, with mention of special talents for each person, reflects the degree of activeness and artistic level of the province. Depending on the appreciating patrons, the audience were indicated as the terms including 'yugaek (party guest),' jwasang,' 'on jwaseok,' and 'sonnim (guests).' It seems that appraisal for a certain performance was very much affected by the tastes, views, and disposition of the appreciating patrons. Therefore it is interesting to observe different comparative reviews of concerts of different regions given by literary figures, offering various criticism on identical performance. In terms of performance space, it has been divided into natural or architectural space, doing justice to special performance sites such as a famous pavilion or an on-the-boat performance. Specific terms related to the scale and brightness of stage, as well as stage props and cast, based on descriptions of performance space were found. The performance space, including famous pavilions; Yeongwangjeong, Bubyeokru, Baeksangru, Wolparu, and Uigeomjeong, which are all well-known tourist sites of Gwanseo province, have been often visited by viceroys. governors, and envoys during a tour or trip. This, and the fact that full-scale performances were regularly held here, and that more than 15 different kinds of boats which were used for boat concert are mentioned, all confirm the general popularity of boat concerts at the time. Performance time, categorized by season or time of day (am/pm/night) and analyzed in terms of time of occurrence and duration, there were no special limitation as to when to have a performance. Most morning concerts were held as part of official duties for the envoys, after their meeting session, whereas evening concerts were more lengthy in duration, with a greater number of people in the audience. In the case of boat concert, samples include day-time concert and performances that began during the day and which lasted till later in the evening. Major terminology related to performance time and season includes descriptions of time of day (morning, evening, night) and mention of sunset, twilight, moonlight, stars, candles, and lamps. Such terms which reflect the flow of time contributed in making a concert more lively. Terminology for the contents of performance was mostly words like 'instrumental,' 'pungak,' or 'pungnyu.' Besides, contextual expressions gave hints as to whether there were dance, singing, ensemble, solo, and duets. Words for dance and singing used in Gwanseo province were almost identical to those used for gasa and jeongjae in the capital, Hanyang. However, many sentences reveal that performances of 'hangjangmu' of hongmunyeon, sword dance, and baettaragi were on a top-quality level. Moreover, chants in hanmun Chinese character and folk songs, which are characteristic for this region, show unique features of local musical performance. It is judged that understanding the purpose and background of a performance is important in grasping the foundation and continuity of local culture. Concerts were usually either related to official protocol for 'greeting,' 'sending-off,' 'reports,' and 'patrols' or for private enjoyment. The rituals for Gwanseo province characteristically features river crossing ceremony on the Daedong river, which has been closely documented by many. What is more, the Gwanseo region featured continued coming and goings of Pyeongan envoys and local officers, as well as ambassadors to and fro China, which required an organized and full-scale performance of music and dance. The method of performance varied from a large-scale, official ones, for which female entertainers and a great banquet in addition to musicians were required, to private gatherings that are more intimate. A performance may take the form of 'taking turns' or 'a competition,' reflecting the dynamic nature of the musical culture at the time. This study, which is deduction of terminology in relation to the time-space and appreciation culture of musical performances of Gwanseo region in late Joseon period, should be expanded in the future into research on 'the performance culture unique to Gwanseo region,' in relation to the financial and administrative aspects of the province, as well as everyday lifestyle. Furthermore, it could proceed to a more intensive research by a comparative study with related literary documents and pictorial data, which could serve as the foundation for understanding the use of space and stage, as well as the performance format characteristic to Korean traditional performing arts.