• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.769-775
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• 2021

The objective of this research was to analyze the factors influencing the farm-gate shrimp prices in Thailand using monthly time series from January 2001 to December 2019. The econometric methodology was employed to satisfy the purpose, consisting of the cointegration test for revealing the long-run relationship and equilibrium elasticity between the variables as well as the error correction model for detecting speed adjustment to shock responses. The empirical results revealed that (1) the export shrimp prices, shrimp production in the country, and shrimp export volume indicated a long-run relationship running to the farm-gate shrimp prices in Thailand with the size of equilibrium elasticity equal to 1.083%, -0.256%, and 0.123, respectively, and (2) the farm-gate shrimp prices in Thailand would adjust to the equilibrium line with a speed equal to 20.147% if there was any kind of incident or shock which caused the relationship to deviate from the equilibrium point. There was no relationship in terms of global shrimp prices and the exchange rate for farm-gate shrimp prices in Thailand. The recommendations should emphasize the varieties of shrimp products for export to other countries beyond the main trading markets nowadays to reduce risks and fluctuations in the export prices of shrimp products.

• Journal of People, Plants, and Environment
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• v.24 no.5
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• pp.529-544
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• 2021

Background and objective: A great deal of previous research has highlighted the value of educational and cultural facilities embedded in housing prices, by taking a large spatial area as the focus, such as the city or district level. However, few studies have investigated the extent to which educational and cultural facilities influence the formation of housing prices from an accessibility perspective. This study aims to identify the value of educational and cultural facilities embedded in the housing prices in Seoul Metropolitan City with a focus on the concept of the residents' neighbourhood and accessibility. Methods: To this end, this research used a spatial regression model with educational and cultural facilities as the independent variables and housing prices as the dependent variable. The model assessed the accessibility of cultural and educational facilities by considering geographic effects. Results: The findings are as follows. First, the spatial error model was found to be the best fit for multi-unit housing, while the spatial lag model was more appropriate for single-unit housing and apartments. Second, private educational facilities and art museums had positive effects on single- and multi-unit housing prices, while historical sites had a negative effect. Finally, private educational facilities positively influenced apartment prices, whereas public libraries and urban park areas had a negative effect. Conclusion: These findings indicate that the accessibility of educational and cultural facilities reflects residents' preferences and needs, which will ultimately influence housing prices.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.225-237
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• 2024

Purpose - This study aims to explore the relationship between housing and land prices, with a specific emphasis on the impact of government policies on these factors such as land supply quantity and the ratio of residential land to total land supplied. The goal is to identify the most effective government intervention strategies for controlling both housing and land prices. Design/methodology/approach - Data from 70 primary and medium-sized cities in China spanning from 2003 to 2017 are utilized in this research. The analysis employs a panel vector autoregressive (PVAR) model, with a primary focus on examining the relationships among housing prices, land prices, and government intervention policies. Findings - Housing and land prices are influenced by various factors. Through impulse response analysis and variance decomposition, it is observed that both housing and land prices are predominantly influenced by their internal dynamics, with comparatively weaker effects attributed to policy interventions. Research implications or Originality - By investigating the impact of government policies on housing and land prices, This study establishes a foundation for effective price control measures. Our study advocates for a comprehensive examination of China's land supply mechanism to enhance understanding of the pathways through which government policies influence the markets.

• Korea Journal of Hospital Management
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• v.28 no.1
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• pp.37-51
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• 2023

Purposes: There exist many non-covered services that the National Health Insurance does not cover, and thus, their prices are set by individual health care providers. However, little study has been done to investigate how hospitals set prices for those services. The purpose of this study is to examine the relationship between ownership, profitability, and prices of those services for a sample of general hospitals. Methodology/Approach: Data regarding the prices of major non-covered services (e.g., upper-level hospital room fees, MRI, Da 7inci robot surgery, and LASIK) were obtained from the Health Insurance Review and Assessment Service and the financial information, as well as other characteristics, were derived from the financial reports from the Korea Health Industry Development Institute. Descriptive statistics, t-tests, and multiple linear regression analyses were used to test the relationship between the independent variables and the dependent variables. Findings: Hospitals owned by private universities appeared to have higher prices for non-covered services while regional public hospitals tend to have lower prices. Profitability, measured by operating margin, was not significantly related to the prices. Hospitals that charge higher prices were more likely to be located in the capital area (Seoul, Incheon, and Gyeonggi), and to employ larger number of personnel. Practical Implications: Public hospitals tend to charge lower prices for non-covered services. Relative market power appears to be related to pricing. Further research is needed to investigate whether such a relationship varies over time and its effects on the quality and access.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4D
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• pp.523-531
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• 2008

This study tried to find differences between housing lotting prices and sale prices owing to new multi-family housing price regulation. As the results of this study, they are as follows; First, this study shows housing market in Busan has a preferences of new housing which has a new housing form differing from the existing housing form. For example, the mixed-use apartment with higher stories shows steeper incline than the apartments with the existing forms. Second, the new housing prices are affected by the information that affect the price of the old existing housing. They are rates of green area of an apartment complex, the number of household, accessibility to downtown Busan and etc.. They are also confirmed factors that affect a rise of used-housing price in other studies. Third, brand value of apartments affects new housing prices. For example, if the major construction companies build the new apartment, it shows a rising trend than any other housing. Therefore, the local construction companies are expected to be put on a disadvantage places than major construction companies. Fourth, the lotting prices are the most important cause that lead to rise the new housing prices. Accordingly, the present lotting prices are expected that upward tendency the purchasing prices of the new housing will not continue, because the lotting prices have risen since the government removed lotting price regulations and exceeded the level of used-housing prices. And it denote that importance of housing sub-market which indicates rates of old existing housing market rising, frist preference Gu, second preference Gu, rate of multi-family housing.

• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.4
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• pp.33-53
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• 2010

When purchase prices of a raw material fluctuate over time, the total purchasing cost is mainly affected by reordering time. Existing researches focus on deciding the right time when the demand for each period is replenished at the lowest cost. However, the decision is based on expected future prices which usually turn out to include some error. This discrepancy between expected prices and actual prices deteriorates the performance of inventory models dealing with fluctuating purchase prices. In this paper, we propose a new inventory model which incorporates not only cost but also risk into making up a replenishment schedule to meet each period's demand. For each replenishment schedule, the risk is defined to be the variance of its total cost. By introducing the risk into the objective function, the variability of the total cost can be mitigated, and eventually more stable replenishment schedule will be obtained. According to experimental results from crude oil inventory management, the proposed model showed better performance over other models in respect of variability and cost.

• Journal of the Korean Regional Science Association
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• v.15 no.3
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• pp.33-51
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• 1999

After the 1997 currency crisis, the real estate prices had been rapidly dropped and the deregulation in the Korean real estate merket has been performed. It is analyzed whether these transactions caused a structural change in real estate market, or not. The Pettitt test shows there exists a turing point in real estate prices in 1998. It is found that the degrees of co-movement between the change in real estate prices and real GDP growth rate are increased. Consequently, the factor, represented as real GDP growth rate, determining the market fundamental of real estate prices will effect on the behavioral pattern and the real estate prices in the long run. While the factors determining the portfolio selection behaviors, such as interest rate and stock prices, will cause short-term variations.

• Journal of Information Technology Applications and Management
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• v.12 no.1
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• pp.141-155
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• 2005

It is very important that sellers provide reasonable reserve prices for auction items in internet auction systems. Recently, an agent has been proposed to generate reserve prices automatically based on the case similarity of information retrieval theory and the moving average of time series analysis. However, one problem of the previous approaches is that the recent trend of auction prices is not well reflected on the generated reserve prices, because it simply provides the bid price of the most similar item or an average price of some similar items using the past auction data. In this paper. in order to overcome the problem. we propose a method that generates reserve prices based on the moving average. the exponential smoothing, and the least square of time series analysis. Through performance experiments. we show that the successful bid rate of the new method can be increased by preventing sellers from making unreasonable reserve prices compared with the previous methods.

• KDI Journal of Economic Policy
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• v.29 no.1
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• pp.113-136
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• 2007

Korean house prices have risen rapidly since year 2001 and there have been some worries that the recent house price hikes are too excessive. This paper empirically analyzes the movement of Korean house prices and derives some implications from it, based on three different theoretical asset pricing models; long-run supply demand model, present value model and general asset pricing model. The results from the analyses show that recent house prices are overall higher than the theoretical prices, thus requiring measures to stabilize house prices hikes.

• KIEE International Transactions on Power Engineering
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• v.4A no.3
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• pp.159-166
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• 2004

Forecasting prices in electricity markets is critical for consumers and producers in planning their operations and managing their price risk. We utilize the generalized autoregressive conditionally heteroskedastic (GARCH) method to forecast the electricity prices in two regions of New York： New York City and Central New York State. We contrast the one-day forecasts of the GARCH against techniques such as dynamic regression, transfer function models, and exponential smoothing. We also examine the effect on our forecasting of omitting some of the extreme values in the electricity prices. We show that accounting for the extreme values and the heteroskedactic variance in the electricity price time-series can significantly improve the accuracy of the forecasting. Additionally, we document the higher volatility in New York City electricity prices. Differences in volatility between regions are important in the pricing of electricity options and for analyzing market performance.