• KDI Journal of Economic Policy
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• v.12 no.1
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• pp.69-91
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• 1990

A major change in tariff rates was made in January 1989 in Korea. The benchmark tariff rate, which applies to about two thirds of all commodity items, was lowered to 15 percent from 20 percent. In addition, the variation in tariff rates among different types of commodities was reduced. This paper examines the economic impact of the tariff reform using a multisectoral general equilibrium model of the Korean economy which was introduced by Lee and Chang(1988), and by Lee(1988). More specifically, this paper attempts to find the changes in imports, exports, domestic production, consumption, prices, and employment in 31 different sectors of the economy induced by the reform in tariff rates. The policy simulations are made according to three different methods. First, tariff changes in industries are calculated strictly according to the change in legal tariff rates, which tend to over-estimate the size of the tariff reduction given the tariff-drawback system and tariff exemption applied to various import items. Second, tariff changes in industries are obtained by dividing the estimated tariff revenues of each industry by the estimated imports for that industry, which are often called actual tariff rates. According to the first method, the import-weighted average tariff rate is lowered from 15.2% to 10.2%, while the second method changes the average tariff rate from 6.2% to 4.2%. In the third method, the tariff-drawback system is internalized in the model. This paper reports the results of the policy simulation according to all three methods, comparing them with one another. It is argued that the second method yields the most realistic estimate of the changes in macro-economic variables, while the third method is useful in delineating the differences in impact across industries. The findings, according to the second method, show that the tariff reform induces more imports in most sectors. Garments, leather products, and wood products are those industries in which imports increase by more than 5 percent. On the other hand, imports in agricultural, mining and service sectors are least affected. Domestic production increases in all sectors except the following: leather products, non-metalic products, chemicals, paper and paper products, and wood-product industries. The increase in production and employment is largest in export industries, followed by service industries. An impact on macroeconomic variables is also simulated. The tariff reform increases nominal GNP by 0.26 percent, lowers the consumer price index by 0.49 percent, increases employment by 0.24 percent, and worsens the trade balance by 480 million US dollars, through a rise in exports of 540 million US dollars and a rise in imports of 1.02 billion US dollars.

• Korean Journal of Ichthyology
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• v.23 no.3
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• pp.234-241
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• 2011

Habitat, reproduction and feeding habit of endangered fish Koreocobitis naktongensis from Jaho stream, Gyeongsangbuk-do, Korea were investigated from March 2010 to June 2011. This species inhabits at the upper and middle parts of stream, which were composed of cobbles and pebbles bottom. The current velocities in these microhabitat were 5~10 cm/sec and depth were 50~110cm. The sex ratio of female to male was 1 : 0.92. It is presumed that the spawning season is from May to June when water temperatures were 17 ~ 20$^{\circ}C$. The average number of mature eggs in ovary were about 22,643 (15,909~30,323), mean egg diameter was 0.87${\pm}$0.05mm. K. naktongensis fed mainly on Chironomidae (IRI, 72.0%) and Ephydridae (26.9%) of Diptera.

• Fire Science and Engineering
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• v.28 no.2
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• pp.69-75
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• 2014

This study derives the factors which affect the occurrence of arson from statistical data (population, economic, and social factors) by multiple regression analysis. Multiple regression analysis applies to 4 forms of functions, linear functions, semi-log functions, inverse log functions, and dual log functions. Also analysis respectively functions by using the stepwise progress which considered selection and deletion of the independent variable factors by each steps. In order to solve a problem of multiple regression analysis, autocorrelation and multicollinearity, Variance Inflation Factor (VIF) and the Durbin-Watson coefficient were considered. Through the analysis, the optimal model was determined by adjusted Rsquared which means statistical significance used determination, Adjusted R-squared of linear function is scored 0.935 (93.5%), the highest of the 4 forms of function, and so linear function is the optimal model in this study. Then interpretation to the optimal model is conducted. As a result of the analysis, the factors affecting the arson were resulted in lines, the incidence of crime (0.829), the general divorce rate (0.151), the financial autonomy rate (0.149), and the consumer price index (0.099).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6315-6324
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• 2015

This study analyses the effects of household finances on rental price of apartment in Seoul which play a major role in real estate policy. We estimate VAR models using time series data. Economy variables such as sales price of apartment in Seoul, consumer price index, hiring rate, real GNI and loan amount of housing mortgage, which relate to household finances and influence the rental price of apartment, are used for estimation. The main findings are as follows. In the short term, the rental price of apartment is impacted by economy variables. Specifically, Relative contributions of variation in rental price of apartment through structural shock of economy variables are most influenced by their own. However, in the long term, household variables are more influential to the rental price of apartment. These results are expected to contribute to establish housing price stabilization policies through understanding the relationship between economy variables and rental price of apartment.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.161-166
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• 2021

The macroeconomic concept represents the movement of a country's economy, and it affects the overall economic activities of business, government, and households. In the macroeconomy, by looking at changes in national income, inflation, unemployment, currency, interest rates, and raw materials, it is possible to understand the effects of economic actors' actions and interactions on the prices of products and services. The US Federal Reserve System (FED) is leading the world economy by offering various stimulus measures to overcome the corona economic recession. Although the stock price continued to decline on March 20, 2020 due to the current economic recession caused by the corona, the US S&P 500 index began rebounding after March 23 and to 3,694.62 as of December 15 due to quantitative easing, a powerful stimulus for the FED. Therefore, the FED's economic stimulus measures based on macroeconomic indicators are more influencing, rather than judging the stock price forecast from the corporate financial statements. Therefore, this study was conducted to reduce losses in stock investment and establish sound investment by analyzing the FED's economic stimulus measures and its effect on stock prices.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.19-43
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• 2016

This study examines the causes of the Asian exchange rate crisis and compares it to the European Monetary System crisis. In 1997, emerging countries in Asia experienced financial crises. Previously in 1992, currencies in the European Monetary System had undergone the same experience. This was followed by Mexico in 1994. The objective of this paper lies in the generation of useful insights from these crises. This research presents a comparison of South Korea, United Kingdom and Mexico, and then compares three different models for prediction. Previous studies of economic crisis focused largely on the manual construction of causal models using linear techniques. However, the weakness of such models stems from the prevalence of nonlinear factors in reality. This paper uses a structural equation model to analyze the causes, followed by a neural network model to circumvent the linear model's weaknesses. The models are examined in the context of predicting exchange rates In this paper, data were quarterly ones, and Consumer Price Index, Gross Domestic Product, Interest Rate, Stock Index, Current Account, Foreign Reserves were independent variables for the prediction. However, time periods of each country's data are different. Lisrel is an emerging method and as such requires a fresh approach to financial crisis prediction model design, along with the flexibility to accommodate unexpected change. This paper indicates the neural network model has the greater prediction performance in Korea, Mexico, and United Kingdom. However, in Korea, the multiple regression shows the better performance. In Mexico, the multiple regression is almost indifferent to the Lisrel. Although Lisrel doesn't show the significant performance, the refined model is expected to show the better result. The structural model in this paper should contain the psychological factor and other invisible areas in the future work. The reason of the low hit ratio is that the alternative model in this paper uses only the financial market data. Thus, we cannot consider the other important part. Korea's hit ratio is lower than that of United Kingdom. So, there must be the other construct that affects the financial market. So does Mexico. However, the United Kingdom's financial market is more influenced and explained by the financial factors than Korea and Mexico.

• Journal of Venture Innovation
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• v.5 no.3
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• pp.71-80
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• 2022

The real estate market is an important part of a country's economy and plays a major role in economic growth through the growth of many related industries. Changes in interest rates affect asset prices and have a significant impact on housing prices. This study analyzed housing prices by dividing them into nationwide, local, and Seoul housing prices in order to analyze whether the effect of changes in interest rates on housing prices shows regional differences. The analysis was conducted from the first quarter of 2011 to the fourth quarter of 2021, and was analyzed using the DOLS model. The main analysis results are as follows. First, interest rates were found to have a significant negative effect on national housing prices, and a drop in interest rates significantly increased national housing prices and an increase in interest rates significantly lowered national housing prices. The consumer price index and loan growth rate also had a positive effect on housing prices nationwide, but statistical significance was not high. Second, interest rates had a negative effect on local housing prices, unlike national housing prices, but were not statistically significant. On the other hand, it was found that the consumer price index and loan growth rate had a larger and significant positive effect on local housing prices compared to national housing prices. Finally, it was found that the interest rate had the only significant negative effect on housing prices in Seoul. And this effect was greater and more significant than the effect on national and local housing prices. In the end, it was found that the effect of interest rates on Korean housing prices differs locally. Interest rates have a significant negative effect on national housing prices, and local housing prices, but they are not statistically significant. In addition, the interest rate was found to have the largest and most significant negative effect on housing prices in Seoul. In addition, it was found that there was a difference in the effect of macroeconomic variables on housing prices. This means that there are differences between regions with different factors influencing local and Seoul housing prices, and this point should be considered when drafting and implementing real estate policies.

• Environmental and Resource Economics Review
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• v.20 no.3
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• pp.531-565
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• 2011

All previous studies analyzing multivariate time series data of EUA (European Union Allowance) price commonly used endogenous variables within the four variables and included the period from April to June of 2006 in the analysis, when the price distortion occurred. This study uses graph theory and structural vector error correction model (SVECM) to analyze the daily time series data of the EUA (European Union Allowance) price. As endogenous variables, five variables are considered for the analysis, including prices of crude oil, natural gas, electricity and coal in addition to carbon price. Data period is Phase 2 period (April 21, 2008 to March 31, 2010) to avoid the EUA price distortion of Phase 1 period (2005~2007). Further, the monthly data including the economic variables as endogenous variables are analyzed.

• International Commerce and Information Review
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• v.13 no.4
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• pp.229-249
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• 2011

The exchange rate change has been increased since the time when the floating exchange rate system was introduced in Korea. As a result, the increase of the exchange rate changes raised the risk in international trades in Korea. Also after Bretton Woods System broke down, the increasing exchange rate fluctuation raised the risk in international trade. The purpose of this dissertation is to study whether this incomplete pass-through exists in Korean export industry and furthermore to measure the markup rate of the export price using real data since Global Financial Crisis. The estimation results of the export price determination model by Error Correction Model shows that the export price of Korea has been greatly influenced by the export prices and exchange rates against U.S. Dollar of rival countries, domestic producer price as well as the Korean Won-U.S. Dollar exchange rate and also business coincidence index of U.S. in demand. Particularly, the pass-through rate of Korean Won-U.S. Dollar exchange rate to export price is estimated to be incomplete, which contrasts with the propositions of traditional exchange rate determination approach, e. g. elasticity approach, monetary approach, etc.

• Current Research on Agriculture and Life Sciences
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• v.4
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• pp.163-168
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• 1986

This study was carried out to compare the conditions of Korean and Japanese forestry. Two countries were appeared same trend in forestry condition, so our forestry in future can be estimated with compared Japanese forestry, but the results obtained are as follows ; 1) The average forest area per capita of the world, Japan and Korea are 0.9, 0.23 and 0.16 ha, respectively, this means that Korean forest area is not sufficient. The growing stock of forest per capita is $22.5m^3$ in Japan and $3.9m^3$ in Korea, but timber consumptions per capita are $1m^3$ in Japan and $0.2m^3$ in Korea. Those mean that both countries have not a plentiful resource of forestry. 2) The forestry production activity becomes gradually stagnation. Both in Korea and Japan, the reforestation and stumpage felling area show gradually decreasing tendency, the artificial forest ratio of total forest area is, at present, 28% in Korea and 40% in Japan. 3) In forestry demand aspect, the ratio of imported timber is 79% in Korea and 62.4% in Japan. Because the price index of timber is lower than the general price index, the dullness of forestry-related industries is expected in future. 4) The forestry labour supply has gradually difficulty because of the reduction in farming labour. 5) The managements of national forests show deficit operation, at present, both in Korea and Japan. The results above mentioned are derived form the poor forest resources, therefore, it is considered that rather more and continuous investment is necessary, but also forestry should be invested in the territorial conservation aspect.