• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.327-337
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• 2017

In this study we compared three models for small area estimation, Fay-Herriot, Hierarchical Bayses model and spatio-temporal model about charter, monthly rent price index. Charter, monthly rent price of Korea are important issue in these days. Because housing type rapidly changes from self to charter and monthly rent. The accuracy of the estimation was checked on four scales, that is ARB, ASRB, AAB, ASD. In this result, the spatio-temporal model among applied models has most optimal scales about small area estimation of charter and monthly rent index.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.1
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• pp.183-201
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• 2022

Estimating the implicit value of housing assets is a very important task for participants in the housing market. Until now, such estimations were usually carried out using multiple regression analysis based on the inherent characteristics of the estate. However, in this paper, we examine the estimation capabilities of the Artificial Neural Network(ANN) and its 'Deep Learning' faculty. To make use of the strength of the neural network model, which allows the recognition of patterns in data by modeling non-linear and complex relationships between variables, this study utilizes geographic coordinates (i.e. longitudinal/latitudinal points) as the locational factor of housing prices. Specifically, we built a dataset including structural and spatiotemporal factors based on the hedonic price model and compared the estimation performance of the models with and without geographic coordinate variables. The results show that high estimation performance can be achieved in ANN by explaining the spatial effect on housing prices through the geographic location.

• The Korean Journal of Applied Statistics
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• v.29 no.3
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• pp.463-470
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• 2016

In analysing a time series on the frequency domain, the spectral estimator (or periodogram) is a very useful statistic to identify the periods of a time series. However, the spectral estimator is very sensitive in nature to outliers, so that the spectral estimator in terms of M-estimation has been studied by some researchers. Pak (2001) proposed an empirical method to choose a tuning parameter for the Huber's M-estimating function. In this article, we try to implement Pak's estimation proposal in the spectral estimator. We use the Korean housing price index as an example data set for comparing various M-estimating results.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.109-118
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• 2023

Data-based analysis methods have become used more for estimating or predicting housing prices, and neural network models and decision trees in the field of big data are also widely used more and more. Neural network models are often evaluated to be superior to existing statistical models in terms of estimation or prediction accuracy. However, there is ambiguity in determining the input feature of the input layer of the neural network model, that is, the type and number of input features, and decision trees are sometimes used to overcome these disadvantages. In this paper, we evaluate the existing methods of using decision trees and propose the method of using decision trees to prioritize input feature selection in neural network models. This can be a complementary or combined analysis method of the neural network model and decision tree, and the validity was confirmed by applying the proposed method to house price estimation. Through several comparisons, it has been summarized that the selection of appropriate input characteristics according to priority can increase the estimation power of the model.

• International Area Studies Review
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• v.14 no.3
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• pp.246-263
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• 2010

This study examines how the long-run relations between housing price and inflation in the United Sates have changed since the year of 2000. Johansen co-integration test, estimation of long-run equilibrium equation, and Granger causality tests are conducted, based on the VECM. Data covers the period from the first quarter of 1975 to the second quarter of 2010. I adopt the recursive estimation method in which the final period of the estimation is expanded by one quarter, starting from the first quarter of 2000. The empirical results are as follows: (1) In spite of the sharp increase of housing price, the long-run relationship of house prices and inflation has been remained stable until 2007, showing that house prices are a stable inflation hedge in the long run. (2) The housing price plunge since 1997 does not seem to be related to the restore of the long-run relationship between housing prices and inflation. (3) Granger causality test results support the hypothesis that inflation granger-causes housing prices with 10% significance level, but reject the hypothesis that housing price granger-causes inflation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.231-241
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• 1999

Recent market competition forces the price to be determined in the design stage so that the design would meet the target price of the product. However, most commercial PDM(Product Data Management) systems currently in use lack such a cost estimation function. In this paper, we propose detailed structure and functions of a new approach to estimate the cost of new products using integrated BOM in PDM. Such system will reduce the total life cycle cost of the products to be designed.

• Geosystem Engineering
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• v.21 no.6
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• pp.297-308
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• 2018

In this paper, we investigate the differences between LNG price of South Korea and Japan. Although S. Korean and Japanese LNG markets have similar structures, there are some differences in the price formation. From DCC-MGARCH, we confirm that Japan LNG price have less persistence of disturbance on time than S. Korean LNG price. The conditional correlation also shows linkage effects between LNG prices and impacts of S-curve and DS-curve. Moreover, ARDL estimation result shows that there is co-integration in all models and that impacts of Fukushima accident and LNG volumes are responsible for the increase in Japanese LNG price. Also, adjustment speed of error correction term shows that Japan's deviation from long-run equilibrium disappears faster than S. Korea does, indicating relatively strong Japanese linkage between LNG price and oil price.

• Environmental and Resource Economics Review
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• v.14 no.4
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• pp.943-964
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• 2005

This study estimated a wide range of stochastic process models using the frameworks of CKLS (1992) and Nowman and Wang (2001). For empirical analysis, the GMM estimation procedure is adopted for the monthly Brent crude oil prices from January 1996 to January 2005. Using the simulated price series, European call option premiums were calculated and compared each other. The empirical results suggest that the crude oil price has a strong dependency of volatility on the price level. Contrary to the results of previous related studies, it shows a weak tendency of mean reversion. In addition, the models provide different implications for pricing derivatives on crude oil.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.585-590
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• 2016

The objective of this study was to develop an export determinant model for laver in the producing district. The annual and monthly amounts of laver products, local price, export price, and foreign exchange rate were included as explanatory variables. The estimation showed that the laver export is influenced more by the long term rather than short term product increase. In addition, as the foreign exchange rate and export price increase, the quantities exported decrease elastically. On the other hand, as the price in the local market increases, the quantities exported decrease non-elastically. Therefore, to enhance the laver exports, it is important to establish infrastructure for long term production increase, forecast and provide information on the export price and foreign exchange rate more accurately.

• Journal of the Korean Home Economics Association
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• v.28 no.1
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• pp.57-66
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• 1990

The purpose of this study was to investigate the analytical model of the implicit price according to objective and subjective characteristics of housing. The hedonic price regression was used for estimating the implicit price. The subjectives of this study were 1,143 dwellers who live in Seoul metropolitan area. Taejeon, and Jeonju. Satistical analyses were conducted using frequencies, percentiles, mean, and multiple regression. The major findings were as follows: 1. There was a significant difference in the implict price of the apartment between owners and renters. 2. There was a sginificant difference in the implicit price of the apartment among Seoul metropolitan area, Taejeon, and Jeonju. 3. Using a stepwise multiple regression method, the order of variables as they were entered in the model were different between tenure types (owner/renter), and regions(Seoul metroplitan area/Taejeon/Jeonju). 4. The linear model was the most appropriate noe which explained the housing price. 5. Subjective characteristics of housing in Taejeon and Jeonju had an effect on the housing price more than those in Seoul metropolitan area.