• Environmental and Resource Economics Review
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• v.15 no.4
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• pp.673-692
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• 2006

In order to test for the dynamic optimality condition for the use of nonrenewable resource, it is necessary to estimate the shadow value of the resource in situ. In the previous literatures, a time series for in situ price has been derived either as the difference between marginal revenue and marginal cost or by differentiating with respect to the quantity of ore extracted the restricted cost function in which the quantity of ore is quasi-fixed. However, not only inconsistent estimates are likely to be generated due to the nonmalleability of capital, but the estimate of marginal revenue will be affected by market power. Since firms will likely fail to minimize the cost of the reproducible inputs subject to market prices under realistic circumstances where imperfect factor markets, strikes, or government regulations are present, the shadow in situ values obtained by estimating the restricted cost function can be biased. This paper provides a valid methodology for checking the dynamic optimality condition for a nonrenewable resource by using the input distance function. Our methodology has some advantages over previous ones: only data on quantities of inputs and outputs are required; nor is the maintained hypothesis of cost minimization required; adoption of linear programming enables us to circumvent autocorrelated errors problem caused by use of time series or panel data. The dynamic optimality condition for domestic coal mining does not hold for constant discount rates ranging from 2 to 20 percent over the period 1970~1993. The dynamic optimality condition also does not hold for variable rates ranging from fourth to four times the real interest rate.

• The Korean Journal of Financial Management
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• v.11 no.1
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• pp.1-29
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• 1994

재무관리의 모든 영역을 완벽하게 이해하기 위하여는 기업재무관리와 투자론을 비롯하여 금융산업 전체에 대한 연역적 방법에 의한 이론의 정립과 실증분석을 통한 이론의 정립이 관건이라 할 수 있다. 이 논문에서는 실증 분석을 수행함에 있어 우리나라에서 활발하게 논의가 진행되지 않는 시계열분석의 영역을 살펴보았다. 그것은 이와 같은 분야를 천착해 봄으로써 이 분야가 재무관리에 대한 통찰력과 현실 적합성의 판단력을 배양하는데 큰 공헌을 할 수 있으리라는 믿음 때문이다. 이 논의를 통하여 시계열 분석에 대한 활발한 연구가 진행되기를 기대하고 있다. 시계열 확률과정에 대한 재무관리이론을 연역적으로 도출하기는 용이하지 않다. 시계열 분석에서 제시되는 여러 방법론을 재무관리의 시계열에 적용하여 그 시계열의 성질과 특성을 파악하면 그것이 그대로 현실에 적용될 수 있을 것이다. 이러한 연구의 결과는 어떤 형태로든 연역적 방법에 의한 이론의 정립에 깊은 영향을 미칠 것이다. 뿐만 아니라 연속시간의 틀과 이시적(異時的) 양태하(樣態下)에서 많은 재무관리 모형들이 개발되고 있으며, 동태적 상황을 해명하는 의도에서 이 모형들이 연구되고 있는 만큼 시계열 분석은 이 분야에 직접적으로 이용될 수 있다. 시계열 분석에서 제시된 많은 모형들이 재무관리의 실증적 현상을 설명하는데 효과적으로 활용될 수 있다. 뿐만 아니라 현재 연역적으로 개발된 모형들이 설명할 수 없는 부분을 시계열 분석이 직접적으로 해명할 수 있는 능력을 확보하고 있음도 제시되었다. 증권의 현가모형(現價模型), 이자율의 기간구조, 효율적 시장가설도 주가의 변동성 등은 시계열 분석의 다양한 기법을 사용하여 검증되어야 하며, 이 경우 특히 분산의 추정방법을 여러 측면에서 개발해 야 할 것이다. 시계열 분석에서는 두개 또는 그 이상의 기법을 하나로 통합하는 방법이 있을 수 있다. ARIMA와 ARCH가 결합되는 것을 본 바 있다. 구조적(構造的) 변화(變化)(structural change)모형(模型)과 ARCH의 결합도 가능하다. 다른 분야로서는 변동성(變動性)에 관한 연구이다. 변동성(變動性)에 관한 연구는 variance bounds test에 한정된 감이 있으나 정보와 변동성의 관계가 중요시되고 있는 만큼 정보집합과 시계열 분석 기법의 결합은 변동성의 연구에 새로운 지평을 열어줄 것으로 보인다. 따라서 정보집합의 형성에 따라 새로운 추정방법이 개발될 여지가 풍부하다.

• Water for future
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• v.14 no.2
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• pp.63-69
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• 1981

This Study is aimed at optimal sequencing of water supply projects for water demand from the application in water resources field of dynamic programming because a minimum present cost strategy for investment in water supply projects plays an important part of installation of some projects. In analysis, the relationships of the future water demand and numerous possible independent projects that are expected to meet water requirements up to some future data in Daegu city were used and future water demand were estimated from the exponential function method, the method used by the Water Works Bureau of Daegu City government which is a kind of geometric progression method and the mean value of these two methods. The results showed that the optimal sequencing of water supply projects using Dynamic Programming was reasonable and the changing of the estimation method of future water demand made a difference among optimal sequence of projects while the changing of annual rate of interest had influenced on present value cost only. In general, the best sequence for constructing the seven projects was the order of D-E-G-F-C-B-A, with the corresponding period for 33-38 years.

• Korean Journal of Construction Engineering and Management
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• v.2 no.2 s.6
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• pp.68-80
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• 2001

While opportunities for international construction firms have been growing with globalization, the risk of international construction projects is significantly increasing in severity and complexity. However, the traditional risk management approach in the construction industry has maintained a profit focus. In addition, this approach has not considered the overall risk at the corporate level, but rather has focused only on the risk of individuals at the project level. Corporate risk management should be implemented from the initial stages of new project selection. This paper suggests the Multi-criteria Integrated Systematic Analysis as a strategic decision-making tool for international construction contractors. The model integrates the multi-criteria of risk, return, and efficiency to choose the optimal set of new portfolios at the corporate level. This model also introduces the Value at Risk (VaR) concept to the international construction industry to present the total risk at the corporate level. To validate this model, this paper tested an experimental case study using the historical data of a global general contractor.

• Journal of Animal Environmental Science
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• v.17 no.sup
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• pp.61-68
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• 2011

To assess the total cost with all stages of facilities, the feasibility of Life Cycle Cost (LCC) analysis was examined in this study to estimate the livestock manure treatment system and optimal decision making process. For the economic evaluation, the plant/equipment investment and annual operation cost of four Public Livestock Recycling Facilities, whose treatment capacity is 100 ton piggery manure per day, was compared. The initial cost was in the range of 2,699 million won to 3,202 million won, where T and E methods were highest and lowest, respectively. The annual operation cost was in the level of 378 million to 498 million won, which decreased in the following order : T method > J method > E method > B method. For the LCC analysis, 4.7% of interest rate, 3.13% of inflation rate, and 1.52% of net discount rate was considered by the data received from Bank of Korea and Statics Korea in the period of 2000 to 2009. Also, for the calculation of present value factor, the durable years of civil engineering & construction, machinery and electric instrument was 30 years, 10 years and 15 years, respectively. Based on these consideration, operation cost was in the range of 17,570 won/ton to 20,661 won/ton, and E method (17,570 won/ton) was economical and B method (20,661 won/ton) was non-economical. Though initial cost of T method was higher than that of B method, LCC analysis of T method was lower than that of T method due to the lower operation cost. Therefore, LCC analysis, which considers both initial cost and operation cost, is more reasonable evaluation method than either initial cost or annual operation cost. For the change of LCC analysis according to the uncertainty, the sensitivity analysis was carried out using fluctuation magnitude of discount rate in the period of 2000 to 2009. As a result, LCC analysis evaluated by discount rate was stable for the uncertain factors since the cost leadership did not change even though the sensitivity analysis varied. In summary, the economic evaluation using LCC analysis could be an efficient reference to choose the suitable livestock manure treatment plants. Furthermore, standardization of statement calculation for the actual cost analysis should be conducted and more detailed study is necessary to validate this summary. Therefore, the application of comprehensive technology evaluation, which considers LCC analysis, should contribute in obtaining objectivity and enhancing reliability for the 'Evaluation of Livestock Manure Treatment System and its Technology'.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.66-79
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• 2016

A discussion has recently emerged over the increase of approvals of K-REITs, which is concluded on the basis of how to raise funds for business activity, fulfill the expected rate of return and maximize the management of managing investment funds. In addition, corporations need to acknowledge the necessity of the capital structure reflected in the current economic environment and decision-making processes. This research analyzed the characteristics by investment types and influence factors about the debt ratio of K-REITs. The data were collected from general management about business state, investment, and finance from 2002 to 2015 in K-REITs (except for the GFC period of 2007~2009). The results of the research demonstrated the high ratios of the largest shareholder characteristics, which are corporation, pension funds, mutual funds, banks, securities, insurance, and, recently, the increasing ratio of the largest shareholder and major stockholder. The investment of K-REITs is increasing the role of institutional investors that take a leading development of K-REITs. The behaviors of simultaneous investment of institutional investors were analyzed to show that they received higher interest rates than other financial institutions and ran in parallel with attraction and compensation. The results of the multiple regressions analysis, utilizing variables about debt ratio were as follows. The debt ratio showed a negative (-) relation that profitability is increasing, which matches the pecking order theory and trade off theory. On the other hand, investment opportunities (growth potential) showed a negative (-) relation and assets scale that indicated a positive (+) relation. The research results are reflected as follows. K-REITs focused on private equity REITs more than public offering REITs, and in the case of financing the capital of others, loan capital is operated under the guarantee of tangible assets (most of real estate) more than financing of the stock market. Further, after the GFC, the capital of others was actively utilized in K-REITs business, and the debt ratio showed that the determinant factors by the ratio and characteristics of the largest shareholder and investment products.

• 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.