• Environmental and Resource Economics Review
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• v.14 no.3
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• pp.699-728
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• 2005

This article is basically an extension of Barten(1993), Brown et al. (1995), Holt and Bishop's(2002) price formation system. A new dynamic price formation system is attempted considering full rationality of the consumers' side. The underlying idea of the new dynamic price formation system is that consumers are rational and farsighted and thus consider past and future consumptions in addition to current consumption to accept the prices traders called. In an empirical application, the U.S. commercial fish demand data are particularly interesting to this analysis in which the species are over fished, including many of the most valuable species. Especially, the grouper-snapper complex are under management jurisdiction of the National Marine Fisheries Council. In the empirical section, it shows how to adapt the model to estimate the marginal values to consumers of commercial fisheries. Since it is conceived of regulations as inducing movements along the marginal value curves, it is of growing importance to regional and national policy makers who are confronted with competing claims on diminishing fish stocks by commercial fisheries interests. It performs well and shows the plausible signs and magnitudes of price flexibilities and interaction among species. It further contributes to the general methodology of applied economics.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.33 no.2
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• pp.117-126
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• 2007

This study investigated the effect of the price and brand name on the consumer's evaluation of cosmetics. 363 women from 20's to 50's living in Seoul and the metropolitan area were asked to use and describe the given samples of cosmetic products for one week with different information of price and brand name. The results of this study are as follows: First, the assessment of the facial toner, moisturizer and cream does not show a significant statistical difference between the group of 'renowned' and 'renownless'. Second, the assessment of the facial toner, moisturizer, and cream shows a significant statistical difference between the user groups which received the prior information whether the cosmetics are 'high price' or 'low price'. Third, the assessment of the users' satisfaction of the 3 kinds of cosmetic products mentioned above is influenced by 'renown' an 'price'. Finally, the interaction of the factor 'renown' and 'price' influences on the cosmetics' effectiveness significantly. From this study, it was discovered that the evaluation and the degree of satisfaction on cosmetics were influenced by the price and brand names. This will improve the understanding of consumers' behavior and personal decision-making, which in be the key of marketing strategy.

• Review of Culture and Economy
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• v.21 no.1
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• pp.85-104
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• 2018

The studies related to the price of artworks have focused on how factors that are determined on production level, such as artists and the artwork materials of the studies, affect the artwork prices. As 'Dansekhwa' is in the spotlight within local Korean art auction matket, this study would like to analyze the trend of the price changes of 'Dansekhwa' with its growing popularity among the public. We have estimated the price changes based on 4,199 auction data of 20 artists with top 20 auction prices selected by the Korean Art Price Appraisal Association, between 2005 and 2016. Also, in order to compare and analyze the price changes of the 'Dansekhwa' products, we have classified the 20 artists into groups of Dansekhwa and non-Dansekhwa. Starting from 2013, when Dansekhwa has first appeared, we applied the Difference in the Difference model(DiD) to estimate the result. As a result, the difference between two groups showed 71% of price difference due to the increase in popularity of Dansekhwa. This result proves that recognition level has an important role for increase in price of an artwork. Moreover, the fact that the formalized style of Dansekhwa has linked to the appreciation of the price means that production of information could play an essential role in growth of art market. As recognition level of Korean artists and their artworks is considerably low within the local art market, putting in the effort to increase the popularity of artworks among the public might be a helpful way to magnify the potential demand.

• Land and Housing Review
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• v.12 no.4
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• pp.41-59
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• 2021

This study reviews theoretical considerations and past studies about real estate prices, macroeconomic variables, and real estate policies. Monthly data from January 2003 to June 2021 are used, and a VEC model, the most widely used multivariate time series analysis method, is employed for analysis. Through the model, the effects of macroeconomic variables and real estate regulatory policies on real estate prices in Seoul are analyzed. Findings are summarized as follows. First, macroeconomic variables such as money supply and interest rates do not have a significant impact on Seoul's apartment prices. Due to the high demand for housing and insufficient supply, there is a demand for buying a home regardless of macroeconomic booms or recessions. Second, tax and financial regulatory policies have an initial impact on the rise in apartment prices in Seoul, and their influence diminishes over time. Third, anti-speculation zones are expected to decrease apartment prices through the suppression of demand. However, these zones cause a rise in apartment prices. This could be understood as a lock-in effect due to the strengthening of capital gains tax. Fourth, the price ceiling did not decrease apartment prices. These findings propose that, in Seoul, where demand is high and supply is insufficient, the supply of high-quality and sufficient housing should be prioritized over various regulations such as tax regulations, financial regulations, anti-speculation zones, and price caps. Moreover, the findings provide an implication that city-specific real estate policies should be implemented for Seoul rather than regulation-oriented approaches in public policy.

• The Transactions of the Korea Information Processing Society
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• v.13 no.5
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• pp.209-216
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• 2024

Real estate market prices are determined by various factors, including macroeconomic variables, as well as the influence of a variety of unstructured text data such as news articles and social media. News articles are a crucial factor in predicting real estate transaction prices as they reflect the economic sentiment of the public. This study utilizes sentiment analysis on news articles to generate a News Sentiment Index score, which is then seamlessly integrated into a real estate price prediction model. To calculate the sentiment index, the content of the articles is first summarized. Then, using AI, the summaries are categorized into positive, negative, and neutral sentiments, and a total score is calculated. This score is then applied to the real estate price prediction model. The models used for real estate price prediction include the Multi-head attention LSTM model and the Vector Auto Regression model. The LSTM prediction model, without applying the News Sentiment Index (NSI), showed Root Mean Square Error (RMSE) values of 0.60, 0.872, and 1.117 for the 1-month, 2-month, and 3-month forecasts, respectively. With the NSI applied, the RMSE values were reduced to 0.40, 0.724, and 1.03 for the same forecast periods. Similarly, the VAR prediction model without the NSI showed RMSE values of 1.6484, 0.6254, and 0.9220 for the 1-month, 2-month, and 3-month forecasts, respectively, while applying the NSI led to RMSE values of 1.1315, 0.3413, and 1.6227 for these periods. These results demonstrate the effectiveness of the proposed model in predicting apartment transaction price index and its ability to forecast real estate market price fluctuations that reflect socio-economic trends.

• Journal of Industrial Convergence
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• v.22 no.6
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• pp.13-23
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• 2024

In this study, the optimal level of CER issuance price in the energy industry was estimated using a real options considering the uncertainty of emission price. As a result of the analysis, the break-even point for CDM projects in the energy industry registered by UNFCCC from December 2012 to the end of 2021 was 0.64-36.69 euros per ton of CO2 for each individual project. More closely, the emission permit price that reaches the break-even point when NPVw/o CER+ NPVCER ≥ 0 is estimated to be 12.10 euros on average, and the emission permit price that reaches the break-even point when NPVw/o CER + NPVCER ≥ option value is estimated to be 12.63 euros on average. Meanwhile, the option value using real options to reduce business uncertainty is about 19% at the 1-5 euro per ton level, about 11% at the 5-10 euro per ton level, and about 5% at the 10-15 euro per ton level. It was analyzed that there was an effect of increasing emissions prices due to uncertainty reduction. The results of this study may be useful to greenhouse gas reduction project entities, including investors, project operators, and companies with potential mandatory reductions.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.472-482
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• 2012

There are many investors in the stock market, and more and more people get interested in the stock investment. In order to avoid risks and make profit in the stock investment, we have to determine several aspects using various information. That is, we have to select profitable stocks and determine appropriate buying/selling prices and holding period. This paper proposes a data mining tool for the investors' decision support. The data mining tool makes stock investors apply machine learning techniques and generate stock price prediction model. Also it helps determine buying/selling prices and holding period. It supports individual investor's own decision making using past data. Using the proposed tool, users can manage stock data, generate their own stock price prediction models, and establish trading policy via investment simulation. Users can select technical indicators which they think affect future stock price. Then they can generate stock price prediction models using the indicators and test the models. They also perform investment simulation using proper models to find appropriate trading policy consisting of buying/selling prices and holding period. Using the proposed data mining tool, stock investors can expect more profit with the help of stock price prediction model and trading policy validated on past data, instead of with an emotional decision.

• Journal of Environmental Policy
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• v.10 no.3
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• pp.49-71
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• 2011

Water is an essential element required for the survival of 6 billion human beings around the world, and it has limited mobility. The importance of water industry has grown considerably, as its forecasted market size is expected to increase from $336 billion in 2007 to $865 billion in 2025, respectively. In 2003, the domestic water market was estimated to be worth 11 trillion won. However, according to the estimates of this research, the result above was overestimated by 2 trillion won. The economic ripple effects of newly defined water industry based on the input-output data from 2000 to 2008 were trivial, as the price effects of water industry was considerably minor at only 0.12%. To successfully implement policies to enhance the water industry, the market price mechanism must operate and function properly. Nevertheless, the impact of water's market prices on the economy upon application is projected to be trivial.

• Environmental and Resource Economics Review
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• v.23 no.4
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• pp.617-641
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• 2014

Korean electricity market is a Cost-Based Pool (CBP) designed to minimize electricity production cost through cost by providing cost reduction incentives to generators. Generation companies have shown diverse efforts to reduce costs in CBP market such as procuring low-price fuels, installing high efficiency gas turbine and constructing power plants near the heavy-load site. Recently, as a way to improve CBP market, a proposal to exclude no-load cost from System Marginal Price (SMP) and to compensate generators ex post was suggested to Korea Power Exchange. This study analyzes the impact of excluding no-load cost from SMP on the cost reduction incentive of generators. We found that excluding no-load cost from SMP enhances the likelihood of decreasing the cost reduction incentives of LNG combined-cycle generators lying on the price-setting range.

• The Journal of the Korea Contents Association
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• v.17 no.8
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• pp.162-174
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• 2017

Product Certification Marks can be used as reliable information in terms of product quality to consumers. This study focuses on how each product attitude of consumers in Korea and China can be changed depending on attachment of product certification mark. Based on nations, product certification marks, and price levels, eight types of questionnaire are distributed and collected where the respondents are allowed to answer product attitudes of two different products in oder to minimize the effect of the product characteristic. As a result, the product attitude of Korean consumers has been showed to more depend on product certification mark than that of Chinese consumers does. The moderating effect of price has been stronger on Chinese consumers than on Korean consumers, and in the case of high price there has been a distinct gap between two countries. This study has its meaning in the way of that the product certification mark has been considered in relation to price level and differently affected product attitude between two countries.