• Title/Summary/Keyword: Price Estimation

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Estimation of Dynamic Effects of Price Increase on Sales Using Bayesian Hierarchical Model (베이지안 다계층모형을 이용한 가격인상에 따른 판매량의 동적변화 추정 및 예측)

  • Jeon, Deok-Bin;Park, Seong-Ho
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2005.05a
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    • pp.798-805
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    • 2005
  • Estimating the effects of price increase on a company's sales is important task faced by managers. If consumer has prior information on price increase or expect it, there would be stockpiling and subsequent drops in sales. In addition, consumer can suppress demand in the short run. Above factors make the sales dynamic and unstable. We develop a time series model to evaluate the sales patterns with stockpiling and short term suppression of demand and also propose a forecasting procedure. For estimation, we use panel data and extend the model to Bayesian hierarchical structure. By borrowing strength across cross-sectional units, this estimation scheme gives more robust and reasonable result than one from the individual estimation. Furthermore, the proposed scheme yields improved predictive power in the forecasting of hold-out sample periods.

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An Estimation of VaR under Price Limits

  • Park, Yun-Sook;Yeo, In-Kwon
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.4
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    • pp.825-835
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    • 2004
  • In this paper, we investigate the estimation of the value at risk(VaR) when stock prices are subjected to price limits. The mixture of probability mass functions and beta density functions is proposed to derive the distribution of asset returns. The analyses of real data show that the proposed distribution is appropriate to explain the VaR when the price limits exist in the data.

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An Empirical Study on the Estimation of Housing Sales Price using Spatiotemporal Autoregressive Model (시공간자기회귀(STAR)모형을 이용한 부동산 가격 추정에 관한 연구)

  • Chun, Hae Jung;Park, Heon Soo
    • Korea Real Estate Review
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    • v.24 no.1
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    • pp.7-14
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    • 2014
  • This study, as the temporal and spatial data for the real price apartment in Seoul from January 2006 to June 2013, empirically compared and analyzed the estimation result of apartment price using OLS by hedonic price model for the problem of space-time correlation, temporal autoregressive model (TAR) considering temporal effect, spatial autoregressive model (SAR) spatial effect and spatiotemporal autoregressive model (STAR) spatiotemporal effect. As a result, the adjusted R-square of STAR model was increased by 10% compared that of OLS model while the root mean squares error (RMSE) was decreased by 18%. Considering temporal and spatial effect, it is observed that the estimation of apartment price is more correct than the existing model. As the result of analyzing STAR model, the apartment price is affected as follows; area for apartment(-), years of apartment(-), dummy of low-rise(-), individual heating (-), city gas(-), dummy of reconstruction(+), stairs(+), size of complex(+). The results of other analysis method were the same. When estimating the price of real estate using STAR model, the government officials can improve policy efficiency and make reasonable investment based on the objective information by grasping trend of real estate market accurately.

A Study on the Determination of Economic Life of Weapon System by using the PRICE Model (PRICE 모텔을 이용한 무기체계 경제수명 결정에 관한 연구)

  • Kim Seung-Soo;Kang Sung-Jin
    • Journal of the military operations research society of Korea
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    • v.30 no.2
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    • pp.13-31
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    • 2004
  • This paper aims at efficient determining the economic life of weapon systems. Specifically, the procedure to estimate the life cycle cost at initial acquisition state or at development state using the PRICE model is proposed. The PRICE model is a parametric cost estimation which is widely used in the field of national defense. The model includes the estimation of the cost in life cycle of weapon systems such as research and development, acquisition, operation and support. Using this model, economic life of weapon systems can be determined. Based on an equivalent annual cost (EAC) method which sums the capital recovery with return (CR) and the equivalence cost (EC), the economic life will be calculated. A case study is accomplished to illustrate the proposed procedure.

ANALYZING THE EFFECT OF THE RESIDENCE AND REAL ESTATE POLICIES ON HOUSING PRICE

  • Jin-Ho Noh;Jae-jun Kim;Sun-Sik Kim;Eun-Jin Ahn;Hye-In Lee;Yoon-Sun Lee
    • International conference on construction engineering and project management
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    • 2007.03a
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    • pp.490-497
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    • 2007
  • Since the foreign currency crisis, Korean economy has suffered recession and the government launches residence and real estate policy in order to increase the demand and trade of real estate and to help the economy revitalization. 1 As a result, the rate of economy growth is shown the high increase with the figure of 10.9% in 1999 and 8.8% in 2000. However, it brings overheating market as a negative effect. Although, the government established the policy for the control of speculation, the policy causes instability of economy. This study is to analyze the effect between the residence policy and the housing cost since the foreign currency crisis through housing sale price estimation and housing lease price estimation and is to apply the basis data of the next residence policy.

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A Study on Properties of Crude Oil Based Derivative Linked Security (유가 연계 파생결합증권의 특성에 대한 연구)

  • Sohn, Kyoung-Woo;Chung, Ji-Yeong
    • Asia-Pacific Journal of Business
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    • v.11 no.3
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    • pp.243-260
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    • 2020
  • Purpose - This paper aims to investigate the properties of crude oil based derivative security (DLS) focusing on step-down type for comprehensive understanding of its risk. Design/methodology/approach - Kernel estimation is conducted to figure out statistical feature of the process of oil price. We simulate oil price paths based on kernel estimation results and derive probabilities of hitting the barrier and early redemption. Findings - The amount of issuance for crude oil based DLS is relatively low when base prices are below $40 while it is high when base prices are around $60 or $100, which is not consistent with kernel estimation results showing that oil futures prices tend to revert toward $46.14 and the mean-reverting speed is faster as oil price is lower. The analysis based on simulated oil price paths reveals that probability of early redemption is below 50% for DLS with high base prices and the ratio of the probability of early redemption to the probability of hitting barrier is remarkably low compared to the case for DLS with low base prices, as the chance of early redemption is deferred. Research implications or Originality - Empirical results imply that the level of the base price is a crucial factor of the risk for DLS, thus introducing a time-varying knock-in barrier, which is similar to adjust the base price, merits consideration to enhance protection for DLS investors.

Comparison of forecasting performance of time series models for the wholesale price of dried red peppers: focused on ARX and EGARCH

  • Lee, Hyungyoug;Hong, Seungjee;Yeo, Minsu
    • Korean Journal of Agricultural Science
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    • v.45 no.4
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    • pp.859-870
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    • 2018
  • Dried red peppers are a staple agricultural product used in Korean cuisine and as such, are an important aspect of agricultural producers' income. Correctly forecasting both their supply and demand situations and price is very important in terms of the producers' income and consumer price stability. The primary objective of this study was to compare the performance of time series forecasting models for dried red peppers in Korea. In this study, three models (an autoregressive model with exogenous variables [ARX], AR-exponential generalized autoregressive conditional heteroscedasticity [EGARCH], and ARX-EGARCH) are presented for forecasting the wholesale price of dried red peppers. As a result of the analysis, it was shown that the ARX model and ARX-EGARCH model, each of which adopt both the rolling window and the adding approach and use the agricultural cooperatives price as the exogenous variable, showed a better forecasting performance compared to the autoregressive model (AR)-EGARCH model. Based on the estimation methods and results, there was no significant difference in the accuracy of the estimation between the rolling window and adding approach. In the case of dried red peppers, there is limitation in building the price forecasting models with a market-structured approach. In this regard, estimating a forecasting model using only price data and identifying the forecast performance can be expected to complement the current pricing forecast model which relies on market shipments.

Estimation of Energy Price Elasticity of per Capita CO2 Emissions under Environmental Kuznets Hypothesis (환경 쿠즈네츠 가설하의 일인당 이산화탄소 배출량의 에너지 가격 탄력성 추정)

  • Lee, Gwanghoon
    • Journal of Environmental Policy
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    • v.11 no.2
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    • pp.55-71
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    • 2012
  • This paper attempts to estimate the energy price elasticity of per capita $CO_2$ emissions, which helps to understand the influence of recent energy price increase on the natural reduction of $CO_2$ emissions. For this purpose, this study researched panel data of twenty-nine OECD countries from 1978 to 2009 and adopted estimation models for testing the environmental Kuznets hypothesis. Estimation results show that the 1% increase of energy price index will cause a statistically significant decrease of per capita $CO_2$ emissions by 0.26 ~ 0.31%, which is substantial enough for policy consideration. Also Kuznet curves in estimation models were identifed, the turning points of income lie between 22.2~48.5 thousand US dollars, depending on model specifications.

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A Study on the Effect of Fisheries Damage Factors on Fisheries Price (어업피해발생요인이 어가에 미친 영향에 관한 연구)

  • Kim, Ki-Soo
    • The Journal of Fisheries Business Administration
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    • v.41 no.2
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    • pp.135-151
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    • 2010
  • Conventional studies concerning about economic evaluation of fisheries damages caused by public undertakings have focused on showing the causality between marin environmental variation and fisheries production. But almost all of them have ignored the effect of fisheries damages factors on fisheries price. The study tries to suggest a model how to examine the existence and measurement of the effect of fisheries damage factors on fisheries price using statistical approach, in other words, the estimation of the statistical coincidence between two different population means. The paper tries to give a good application of the model using the case of fisheries damages caused by oil leakage pollution which happened three years ago in the coast of Taean province.

The Estimation of the Demand Function of Korean Beef and Imported Beef Cuts - Focusing in Consumers in the Metropolitan Area - (한우와 수입산 쇠고기의 부위별 수요함수 추정 - 수도권 소비자를 중심으로 -)

  • Nam, Kuk-Hyun;Choe, Young-Chan
    • Journal of Agricultural Extension & Community Development
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    • v.23 no.4
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    • pp.387-403
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    • 2016
  • This paper estimated the demand function of the cuts of Korean beef and imported beef by using the consumer panel and retail price data from the Korean Agro-Fisheries & Food Trade Corporation, and the weather data from the Korea Meteorological Administration with an log-log model and AIDS model. The results show that the preference for cuts of beef used for cooked soup, steamed dish, Changjorim are more elastic than cuts used for roasting when there is a change in price and income in the estimation of demand function of Korean beef. On the other hand, consumers respond sensitively with the demand of roasting part compared to steamed dish, Changjorim, soup when there is change in price and income in the estimation of demand function of imported beef. The results indicate that there is substitutional relationship between Korean beef and imported beef, because Korean beef cuts used for roasting can substitute for imported roasting part and the same relationship applies to steamed dish, soup, Changjorim. In addition, family number, family member, husband job, purchasing place, means of transportation, purchasing time, weather are statistically significant.