• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.33-40
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• 2020

The main aim of the study is to test a house pricing model by combining hedonic and asset-based pricing models. An understanding of the relationship between house pricing and its return (the rental income) helps to establish houses as a significant asset class. The model tested the relationship between house pricing (dependent variable) and the house attributes (independent variables) derived from Freeman's framework of housing attributes. This study uses a large data-set of 1,899 sample of new, high-end houses purchased between 2016 and 2019 collected from the national capital region of India (Delhi-NCR). The algorithm was built in R-Script, and stepwise multiple linear regression was used to analyze the model. The analysis of the model proves that the three significant variables, namely, carpet area, pay-off, and annual maintenance charges explain the price function. Further, the model is statistically fit. The major contribution of the study is to understand the key factors and their influence on the house pricing. The model will be helpful in risk assessment in the housing investment and enhance the chances of investment. Policy-makers can use information about the underlying valuation drivers of the house prices to stabilize the market and also in framing the tax policies.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1128-1134
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• 2016

Demand response provides customer load reductions based on high market prices or system reliability conditions. One type of demand response, price-based program, induces customers to respond to changes in product rates. However, there are large-scale general and industrial customers that have difficulty changing their energy consumption patterns, even with rate changes, due to their electricity demands being commercial and industrial. This study proposes an in-house pricing model for large-scale general and industrial customers, particularly those with multiple business facilities, for self-regulating demand-side management and cost reduction. The in-house pricing model charges higher rates to customers with lower load factors by employing peak to off-peak ratios in order to reduce maximum demand at each facility. The proposed scheme has been applied to real world and its benefits are demonstrated through an example.

• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.85-93
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• 2011

Many policies, such as transit-oriented development, encouraged use of bicycle and pedestrian, reduction of green house gas (GHG) and etc., have been deployed to support transport sustainability. Although various studies regarding GHG were presented, no one has yet adequately explained the behavior of travelers. This paper proposes a GHG emission model by highlighting its sensitivity, elasticity with regard to such travel cost as travel time, travel fare, and GHG pricing, introduced to reduce the amount of GHG in transportation system. For better estimation of GHG, the proposed model adopts (1) a production-constrained gravity model and (2) the travel distance from the origin and the destination (OD). The gravity model has a merit that it considers travel pattern between OD pairs. The model was tested with an example, and the promising results confirmed its validation and applications.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.175-182
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• 2013

In this paper, the simulation model of house price is presented on the basis of pricing mechanism between the demand and the supply of apartments in seoul. The algorithm of house price simulation model for calculating the rate of price over time includes feedback control theory. The feedback control theory consists of stock variable, flow variable, auxiliary variable and constant variable. We suggest that the future price of apartment is simulated using mutual interaction variables which are demand, supply, price and parameters among them. In this paper we considers three items which include the behavior of apartment price index, the size of demand and supply, and the forecasting of the apartment price in the future economic scenarios. The proposed price simulation model could be used in public needs for developing a house price regulation policy using financial and non-financial aids. And the quantitative simulation model is to be applied in practice with more specific real data and Powersim Software modeling tool.

• Environmental and Resource Economics Review
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• v.31 no.2
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• pp.205-232
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• 2022

This study analyzes the effect of the 2^nd pilot test of Tiime of Use (TOU) pricing for Korean households using a two-level electricity demand model. The test, implemented from May to September 2021, was conducted to compare the effects of two TOU pricing rates and the standard rates for households living in apartment and detached house in 7 provinces of Korea. Based on the data on electricity consumption during the test period and during the same period last year of the 1,292 participants and their socio-economic characteristics, this study analyzes (1) whether the relative demand across periods has changed in response to hourly price changes and (2) whether the price responsiveness of daily consumption has changed after the introduction of TOU pricing. The results show that both types of TOU pricing affect neither the relative demand across periods nor the price responsiveness of daily consumption. The reason behind the results could be related to the level of TOU pricing rates and the periodical classification, which were not sufficient to induce changes in the participants' electricity demand patterns.

• Korean Journal of Construction Engineering and Management
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• v.18 no.6
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• pp.89-97
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• 2017

The number of Aged Apartment units is expected to increase as time went on. Living standards are getting better and they want a new apartment space as the economy progresses. Therefore, it is necessary to prepare for the increasing remodeling market through the feasibility evaluation method that can be applied to the remodeling project of the apartment house. The purpose of this study is to analyze the social pricing factors affecting the Officially assessed individual House Price for the analysis model of commercial house remodeling. The collected samples were analyzed using multiple regression analysis of 350 prices included in 127 lots. Middle school level, high school level, total number of households, and floor area ratio were extracted. As a result of comparing the Officially assessed individual House Price by applying to the remodeling case, the difference between the existing Officially assessed individual House Price and the improvement Officially assessed individual House Price is different. The accessibility with the subway station is included in the land price, and there is no change in the number of stories and directions because it is customized remodeling. There was a difference in the disclosure price depending on the type of factor extraction by the evaluator in a batch application of the disclosure price factors. The research can be used as a model for future remodeling business feasibility analysis.

• Environmental and Resource Economics Review
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• v.29 no.3
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• pp.335-362
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• 2020

Using the Hedonic pricing model using Box-Cox transformation, this paper estimated the marginal effect (implicit price) of odors from landfill in the metropolitan area on housing prices and the willingness to pay for changes in certain odor conditions. This paper utilized the proximity from the landfill in the metropolitan area as a environmental variable, and analyzed the effect of various housing characteristic variables on the sale price of apartments within a radius of 5 km from the landfill. In particular, because odors factor have various heterogeneity, we applied hedonic price models instead of stated-preference methods with various types of functional forms through Box-Cox transformation, considering the heterogeneity of each region. Estimates show that the marginal value (implicit price) for the distance from the odor source was 0.227 to 0.533 depending on the function type of the estimated model. In addition, when other house factors are the same, the marginal willingness to pay for a distance of 1km from the odor source was calculated to be 16.79 to 51.76 thousand dollar depending on the type of function. Finally for the general Box-Cox model, the annual WTP was estimated to be 3,229dollar.

• Journal of Distribution Science
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• v.13 no.8
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• pp.61-71
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• 2015

Purpose - Before the year 2000, the housing prices in Korea were increasing every decade. After 2000, for the first time, Korea experienced a decrease in housing prices, and the repetitive cycle of price fluctuation started. Such a "boom and bust cycle" is a worldwide phenomenon. The current study proposes a mathematical model to explain price fluctuation cycles based on the theory of consumer psychology. Specifically, the model incorporates the effects of buyer expectations of future prices on actual price changes. Based on the model, this study investigates various independent variables affecting the amplitude of price fluctuations in housing markets. Research design, data, and methodology - The study provides theoretical analyses based on a mathematical model. The proposed model uses the following assumptions of the pricing mechanism in housing markets. First, the price of a house at a certain time is affected not only by its current price but also by its expected future price. Second, house investors or buyers cannot predict the exact future price but make a subjective prediction based on observed price changes up to the present. Third, the price is determined by demand changes made in previous time periods. The current study tries to explain the boom-bust cycle in housing markets with a mathematical model and several numerical examples. The model illustrates the effects of consumer price elasticity, consumer sensitivity to price changes, and the sensitivity of prices to demand changes on price fluctuation. Results - The analytical results imply that even without external effects, the boom-bust cycle can occur endogenously due to buyer psychological factors. The model supports the expectation of future price direction as the most important variable causing price fluctuation in housing market. Consumer tendency for making choices based on both the current and expected future price causes repetitive boom-bust cycles in housing markets. Such consumers who respond more sensitively to price changes are shown to make the market more volatile. Consumer price elasticity is shown to be irrelevant to price fluctuations. Conclusions - The mechanism of price fluctuation in the proposed model can be summarized as follows. If a certain external shock causes an initial price increase, consumers perceive it as an ongoing increasing price trend. If the demand increases due to the higher expected price, the price goes up further. However, too high a price cannot be sustained for long, thus the increasing price trend ceases at some point. Once the market loses the momentum of a price increase, the price starts to drop. A price decrease signals a further decrease in a future price, thus the demand decreases further. When the price is perceived as low enough, the direction of the price change is reversed again. Policy makers should be cognizant that the current increase in housing prices due to increased liquidity can pose a serious threat of a sudden price decrease in housing markets.

• Korean Journal of Construction Engineering and Management
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• v.15 no.1
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• pp.111-121
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• 2014

The Clean Development Mechanism (CDM) allows New & Renewable Energy projects to make additional income by selling CER's, which represent the amount of Green House Gases(GHG) that is reduced in the project. However, forward contracts used to hedge fluctuating market prices does not allow projects to sell CER's at a premium. As an alternate approach to maximize CER revenue, CER's are modeled as a 'real option', in which CER's are sold only above the desired sales price. Using the Binomial Option Pricing model, the resultant lattices are used to determine whether to sell, defer or abandon the option at individual nodes. Overlaying Pascal's Triangle on the lattices also enabled the calculation of the annual probabilities for deferring CER sales without incurring downside losses. Application to an actual Landfill Gas project showed increased overall NPV, and that CER sales could be deferred at a maximum of 2 years. The proposed framework allows transparency in the analysis and provides valuable and strategical information when making investment decisions related to CER sales of CDM projects.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.2038-2045
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• 2010

Households' monthly average income is composed of various factors. This study paper studies focuses on estimating the determinants of a households' monthly average income. The region for analysis consist of three groups, that is, the whole country, a metropolitan city(such as Busan, Daegu, Incheon, Gwangiu, Daejeon, Ulsan.) and Seoul. Analyzing period be formed over a 57 time points(2005. 01~2009. 09). In this paper the dependent variable setting up the households' monthly average income, explanatory (independent) variables are composed of the consumer price index, employment to population ratio, Index of housing sale price, the preceding composite index, loans of housing mortgage, spending rate for care medical expense and the composite stock price index. In looking at the factors which determine the monthly average income, evidence was produced supporting the hypothesis that there is a significant positive relationship between the composite index and housing loans. The study also produced evidence supporting the view that there is a significant negative relationship between employment ratios, the house sale pricing index and spending rates for care or medical needs. The study found that the consumer price index and composite stock price index were not significant variables. The implications of these findings are discussed for further research.