• Land and Housing Review
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• v.13 no.4
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• pp.45-53
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• 2022

This paper investigates empirically the lead-lag relation between the 'apartment price index' and 'Internet search volume'. This study uses Naver Trend Index as a proxy for Internet search volume. An increase in Internet search volume on the apartment price index indicates an increase in people's attention to an apartment. Different from previous studies exploring the relation between 'the released price index of the apartment' and 'Naver Trend Index', this study investigates the relation of the Naver Trend Index with 'the fundamental price component of an apartment' and 'the transitory price component of an apartment', respectively. The results of the Granger causality test reveal that there are bidirectional Granger causalities between the 'released price' and Naver Trend Index. In addition, the 'fundamental price component of an apartment' and Naver Trend Index have a feedback relation, while 'the transitory price component of an apartment' Granger causes the Naver Trend Index uni-directionally. The impulse response function analysis indicates that the shock of apartment prices increases Naver Trend Index in the first month. Overall, The close relationship between apartment prices and Naver Trend Index suggests that increases in the movement of apartment prices are positively associated with public attention on the apartment market.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.543-556
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• 2001

This study suggests integrated neural network modes for he stock price index forecasting using change-point detection. The basic concept of this proposed model is to obtain significant intervals occurred by change points, identify them as change-point groups, and reflect them in stock price index forecasting. The model is composed of three phases. The first phase is to detect successive structural changes in stock price index dataset. The second phase is to forecast change-point group with various data mining classifiers. The final phase is to forecast the stock price index with backpropagation neural networks. The proposed model is applied to the stock price index forecasting. This study then examines the predictability of integrated neural network models and compares the performance of data mining classifiers.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.211-231
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• 2022

This study attempted to identify the effects of macroeconomic variables such as the All Industry Production Index, Consumer Price Index, CD Interest Rate, and KOSPI on apartment lease prices divided into nationwide, Seoul, metropolitan, and region, and to present a methodological prediction model of apartment lease prices by region using Long Short Term Memory (LSTM). According to VAR analysis results, the nationwide apartment lease price index and consumer price index in Lag1 and 2 had a significant effect on the nationwide apartment lease price, and likewise, the Seoul apartment lease price index, the consumer price index, and the CD interest rate in Lag1 and 2 affect the apartment lease price in Seoul. In addition, it was confirmed that the wide-area apartment jeonse price index and the consumer price index had a significant effect on Lag1, and the local apartment jeonse price index and the consumer price index had a significant effect on Lag1. As a result of the establishment of the LSTM prediction model, the predictive power was the highest with RMSE 0.008, MAE 0.006, and R-Suared values of 0.999 for the local apartment lease price prediction model. In the future, it is expected that more meaningful results can be obtained by applying an advanced model based on deep learning, including major policy variables

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.197-204
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• 2020

Nowadays, many construction engineering and technology enterprises are evolving to find that prosperity is driven and inspired by an open economy with dynamic markets and fierce multifaceted competition. Besides brand and product uniqueness, the ability to quickly provide customers with quotes are matters of concern. Such a requirement for prompt cost estimation of construction investment projects with the use of a construction price index poses a significant challenge to contractors. This is because the nature of the construction industry is shaped by changes in domestic and foreign economic factors, socio-financial issues, and is under the influence of various micro and macro factors. This paper presents a fuzzy decision-making approach for calculating critical factors that affect the construction price index. A qualitative approach was implemented based on in-depth interviews of experts in the construction industry in Vietnam. A synthetic comparison matrix was calculated using Buckley approach. The CoA approach was applied to defuzzified the fuzzy weights of factors that affect the construction price index. The research results show that the top five critical factors affecting the construction price index in Vietnam are (1) consumer price index, (2) gross domestic product, (3) basic interest rate, (4) foreign exchange rate, and (5) total export and import.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1471-1479
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• 2017

The variability of trade price index of apartment influences on the various aspect, especially economics, social phenomenon, industry, and culture of the country. In this article, the autoregressive error (ARE) model has been considered for analyzing the monthly trading price index of apartment data. About 16 years of the monthly data have been used from September 2001 to May 2017. In the ARE model, six macroeconomic variables are used as the explanatory variables for the rade price index of apartment. The six explanatory variables are mortgage rate, oil import price index, consumer price index, KOSPI stock index, GDP, and GNI. The result has shown that trading price index of apartment explained about 76% by the mortgage rate, and KOSPI stock index.

• Proceedings of the Korean Institute of Building Construction Conference
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• v.y2004m10
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• pp.83-86
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• 2004

Index adjusted ration method has been widely utilized in public construction secter for contract sum adjustment by price fluctuation. In this method. the Production Price Index are used for calculating the base ratio. but the PPI can't reflect the property of construction project in respect of the selected item and weight structure. In this research we prove the problem of using the index adjusted ration method in contract sum adjustment by price fluctuation. and improve it by using the construction cost index. which has the property of construction project. And the result. we figure out the difference between the PPI and CCI by $6.7\%$ in maximum value.

• Journal of Korean Academy of Nursing Administration
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• v.10 no.1
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• pp.1-9
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• 2004

Korean health insurance has adopted preliminary DRG payment system through 8 DRGs from 1997. But present DRG payment system gives economic incentives for hospitals to hire less nurse. This study was attempted to develope DRG adjust index to differentiate DRG price by nurse staffing level for nursing care quality. Method: We analyzed inpatient care cost by medical institute and developed DRG adjust index to differentiate DRG price by nurse staffing level. Results: Among same medical institute, inpatient care cost are very different according to hospital's nurse staffing level. In the case of casarean section, inpatient care cost of the 1st grade general hospital are more expensive 85,732won than the 6th grade hospital. The cost difference are 8.24% of total casarean section DRG price and 16.48% of DTG variable price. We developed DRG adjust index-a to apply DRG variable price and index-b to apply DRG total price for compensation cost difference of hospitals. Conclusions: DRG price adjust index will give economic incentive for hospitals to hire more nurse and improve nursing care quality.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.195-200
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• 2021

In recent years, Vietnam's economic growth rate has been attributed to the growth of many well-managed industries within Southeast Asia. Among them is the civil construction industry. Construction projects typically take a long time to complete and require a huge budget. Many socio-economic variables and factors affect total construction project costs due to market fluctuations. In recent years, crucial socioeconomic development indicators of construction reached a fairly high growth rate. Also, most infrastructure and construction projects have a high degree of complexity and uncertainty. This makes it challenging to predict the accurate project price. These challenges raise the need to recognize significant factors that influence the construction price index of civil buildings in Vietnam, both micro and macro. Therefore, this paper presents critical factors that affect the construction price index using the fuzzy extent analysis process in an uncertain environment. This proposed quantitative model is expected to reflect the uncertainty in the process of evaluating and ranking the influencing factors of the construction price index in Vietnam. The research results would also allow project stakeholders to be more informed of the factors affecting the construction price index in the context of Vietnam's civil construction industry. They also enable construction contractors to estimate project costs and bid rates better, enhancing their project and risk management performance.

• Journal of The Korean Digital Architecture Interior Association
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• v.10 no.2
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• pp.13-20
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• 2010

Uncertainty in housing price fluctuation has great impact on the overall economy due to importance of housing market as both place of residence and investment target. Therefore, estimating housing market condition is a highly important task in terms of setting national policy. Primary indicator of the housing market is a ratio between rent and transaction price of housing. The research explores dynamic relationships between Rent-Transaction price ratio, housing transaction price and jeonse rental price, using Vector Autoregressive Model, in order to demonstrate significance of shifting rent-transaction price that is subject to changes in housing transaction and housing rental market. The research applied housing transaction price index and housing rental price index as an indicator to measure transaction and rental price of housing. The price index and data for price ratio was derived from statistical data of the Kookmin Bank. The time-series data contains monthly data ranging between January 1999 and November 2009; the data was log transformed to convert to level variable. The analysis result suggests that the rising ratio between rent-transaction price of housing should be interpreted as a precursor for rise of housing transaction price, rather than judging as a mere indicator of a current trend.

• Journal of Korean Society of Rural Planning
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• v.28 no.4
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• pp.69-81
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• 2022

The change in farmland price has almost always been focused on not only farmers but policy-decision makers; for farmers to get information before purchasing farmland; for policy-decision makers to use appropriate policy tools to stabilize the market. So far the change in farmland price has been calculated as a form of average change on a year-to-year base. Such calculations have become one of the causes which lead to misunderstanding of the farmland market because the year-to-year average change includes changes in price as well as changes in the number of trades and sizes of traded farmland. This paper is designed to suggest a proper method of building a price index for farmland as a tool to review the price change. We considered the applicability of several types of price indices and concluded that a Laspeyres-type price index is the most reasonable choice. A Laspeyres-type price index, however, has a shortcoming in which a reference year's weight may affect the whole period of an index. Thus, we also suggest two other weights, a three-year average including a reference year and a share of farmland. All indices show that farmland prices have risen significantly in recent 10 years. We hope that the indices will be developed into one of the government's formal statistics.