• Korea Trade Review
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• v.48 no.2
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• pp.71-94
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• 2023

The purpose of this study is to prove the effect of psychic distance between home country and host country on overseas foreign direct investment(OFDI) of Spanish companies through panel analysis. The panel data was based on cultural, institutional, economic, and geographical distance data over the past decade between Spain and Spain's OFDI countries. According to the Random Effect Model(REM) analysis, cultural distance(CULD) had a negative effect on OFDI, while institutional distance(INSD) had a positive effect. Among economic distances, income size distance(GDP) had a positive effect on OFDI, but export size distance(EXPO) had a negative effect. Geographic distance(PKM) had a negative impact. Meanwhile, according to the results of quantile regression analysis to prove the psychic distance effect by OFDI size, the effects of CULD and INSD in the quartile (75%) to which Korea belongs were the same as the REM analysis results. In addition, GDP and EXPO had a positive effect, and PKM had a negative effect but EXPO had a positive effect. Therefore, FDI host countries need to establish differentiated strategies through quantile analysis while making continuous efforts to improve the system.

• Journal of Korean Society of Rural Planning
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• v.28 no.2
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• pp.41-50
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• 2022

The primary purpose of this study is to identify various factors that affect farmland prices according to changes in the actual transaction price of farmland over the past decade, and to use this to derive policy implications for price stabilization. To this end, the farmland price model are constructed at the parcel level in the case area (Namwon-si, Jinju-si). The analysis method is based on the Hedonic price function, and the OLS and the quantile regression are used for the parcel level model. As a result of estimating the parcel level farmland price model in the case area, the larger the parcel area, the lower the farmland price, and the higher the farmland price outside the agricultural promotion area. It was found that there was a price difference according to the type of special purpose areas, and the location characteristics showed some differences across the cities. The farmland price models presented in this study are suitable for identifying the factors affecting farmland prices, and are expected to be highly utilized in that it is possible to construct flexible variables suitable for regional characteristics.

• Environmental and Resource Economics Review
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• v.27 no.1
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• pp.195-214
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• 2018

This study estimates the price elasticity of residential water demand in Korea. For that, annual panel data from the year of 2010 to 2013 for 161 local water services is estimated by using panel quantile model. As a result, the price elasticities of residental water demand in Korea are estimated to be between -0.156 and -0.189 depending on its quantile. In addition, the study finds that the estimated elasticity of residential water demand by traditional conditional mean regression is relatively more influenced by high demand areas because the distribution of residental water demand in Korea is left-skewed.

• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.264-272
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• 2019

In this paper, we propose a 3D human body reconstruction and refinement method from the frames extracted from a video to obtain natural and smooth motion in temporal domain. Individual frames extracted from the video are fed into convolutional neural network to estimate the location of the joint and the silhouette of the human body. This is done by projecting the parameter-based 3D deformable model to 2D image and by estimating the value of the optimal parameters. If the reconstruction process for each frame is performed independently, temporal consistency of human pose and shape cannot be guaranteed, yielding an inaccurate result. To alleviate this problem, the proposed method analyzes and interpolates the principal component parameters of the 3D morphable model reconstructed from each individual frame. Experimental result shows that the erroneous frames are corrected and refined by utilizing the relation between the previous and the next frames to obtain the improved 3D human reconstruction result.

• The Journal of the Korea Contents Association
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• v.16 no.2
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• pp.729-739
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• 2016

The primary objective of implementing the study was to further investigate any pronounced financial components affecting the level of cash retention for the Korean chaebol firms. The research was framed to test for two hypotheses on the cash savings with utilizing the chaebol firms during the post-era of the global financial turmoil (from 2009 to 2013). In the first hypothesis test, any significant explanatory variables relative to the cash holdings, were identified in each corresponding category of the conditional quantile regression (CQR) model, while multilogistic regression analysis was performed to discriminate relevant financial factors in each pair of classes consisting of the chaebol firms. Concerning the results, liquidity, agency costs, and cash conversion cycle were found to be statistically significant in the majority of classified categories in the former test and liquidy, firm size, and dividend yield, also showed discriminating powers in each pair of categorical for the firms in the latter test.

• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.83-92
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• 2015

Concerning the national health, it is important to develop an accurate prediction method of atmospheric particulate matter (PM) because being exposed to such fine dust can trigger not only respiratory diseases as well as dermatoses, ophthalmopathies and cardiovascular diseases. The National Institute of Environmental Research (NIER) employs a decision tree to predict bad weather days with a high PM concentration. However, the decision tree method (even with the inherent unstableness) cannot be a suitable model to predict bad weather days which represent only 4% of the entire data. In this paper, while presenting the inaccuracy and inappropriateness of the method used by the NIER, we present the utility of a new prediction model which adopts boosting with quantile loss functions. We evaluate the performance of the new method over various ${\tau}$-value's and justify the proposed method through comparison.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.444-453
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• 2018

The study addresses the analysis on the financial determinants of corporate research and development (R&D) expenditure in finance. Overall level of R&D spending was estimated as one of the top-tier on a global basis and a majority of the expenditure was invested by large domestic firms in private sector. Consequently, financial factors that influence R&D intensity were empirically tested in the first hypothesis by using conditional quantile regression model for firms listed in KOSPI stock market in the post-era of the global financial turmoil. Firms in the groups of high- and low-R&D intensity were statistically compared to detect financial differences in the second hypothesis which was accompanied by the test of multi-logit model that included firms without R&D outlay. Concerning the results of the hypothesis tests, R&D spending of the prior fiscal year, firm size, business risk and advertising expense overall showed statistically significant impacts to determine the level. As an extended study of [1] that had examined financial factors of R&D intensity at the macro-level, the results of the present study are anticipated to contribute to maximizing shareholders' wealth in advance or emerging capital markets, when applied to find an optimal level of R&D expenditure.

• The Journal of the Korea Contents Association
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• v.14 no.12
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• pp.973-988
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• 2014

This study investigated one of the contemporary issues in the Korean capital market and two hypotheses of concern were tested on the financial determinants of profitability for the firms belonging to the Korean chaebols during the era of the post-global financial turmoil. The first hypothesis applying conditional quantile regression (CQR) estimation provided the evidence that leverage ratio, fixed asset utilization, and foreign ownership among the nine quantitative explanatory variables, had overall statistical significance relative to the book-valued profitability measure, while additional variables such as a firm's size, fixed and a proxy for the type of exchange market showed their strong impacts on the market-valued profitability indicator. Concerning the formulated 'extended' DuPont system, only two components of EBITDAEBIT and EMULTIPLIER revealed their prominent influence on ROE (Return on Equity) over the two tested periods (the years 2008 and 2012).

• Journal of Korea Water Resources Association
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• v.42 no.6
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• pp.465-480
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• 2009

In this study, single and multiple linear regression model were used to derive the relationship between precipitation and altitude, latitude and longitude in Jejudo. The single linear regression analysis was focused on whether orographic effect was existed in Jejudo by annual average precipitation, and the multiple linear regression analysis on whether orographic effect was applied to each duration and return period of quantile from regional frequency analysis by index flood method. As results of the regression analysis, it shows the relationship between altitude and precipitation strongly form a linear relationship as the length of duration and return period increase. The multiple linear regression precipitation estimates(which used altitude, latitude, and longitude information) were found to be more reasonable than estimates obtained using altitude only or altitude-latitude and altitude-longitude. Especially, as results of spatial distribution analysis by kriging method using GIS, it also provides realistic estimates for precipitation that the precipitation was occurred the southeast region as real climate of Jejudo. However, the accuracy of regression model was decrease which derived a short duration of precipitation or estimated high region precipitation even had long duration. Consequently the other factor caused orographic effect would be needed to estimate precipitation to improve accuracy.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.23-23
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• 2018

본 연구에서는 다중분위회귀분석모형(Multiple Quantile Regression Model, MQRM)과 MODIS(MODerate resolution Imaging Spectroradiometer) LST (Land Surface Temperature) 자료를 이용하여 전국 공간토양수분을 산정하였다. 공간토양수분을 산정하기 위한 과정은 크게 두가지로 구분된다. 첫 번째로 기존의 MODIS LST 자료를 조건부 합성 보정기법을 적용하여 실측 LST 자료와 비교하여 위성 LST 자료가 갖고 있는 오차를 보정하였다. 그 결과, 조건부 합성 보정기법을 적용하기전 전국 71개 지상관측지점에서 관측한 실측 LST와 MODIS LST의 $R^2$는 전체 평균 0.70으로 어는정도 유의성 있는 상관관계를 나타냈으나 조건부 합성 보정기법을 적용한 후 실측 LST와 MODIS LST의 $R^2$는 전체 평균 0.92로 상당히 크게 향상됨을 알 수 있었다. 두 번째로 보정된 MODIS LST를 이용하여 다중분위회귀분석 모형을 개발하고 토양수분을 예측하는 단계로 입력자료로 위성영상 자료와 관측자료를 융합하여 사용하였다. 위성영상 자료로는 보정된 MODIS LST와 MODIS NDV를 구축하였고 일단위 강수량 및 일조시간의 기상자료는 기상청으로부터 전국 71개 지점에 대해 구축하여 IDW 공간보간기법을 이용한 공간자료로 구축하였다. 토양수분 결과를 비교하기 위한 관측 토양수분은 자동농업기상관측(Automated Agriculture Observing System, AAOS)지점에서 2013년 1월부터 2015년 12월까지의 실측 일단위 토양수분 자료를 구축하여 사용하였다. 다중분위회귀분석 모형은 LST 인자를 중심으로 각각의 분위(0.05, 0.25, 0.5, 0.75, 0.95)에 해당되는 값의 회귀식을 NDVI, 강수 입력자료를 독립인자로서 조합하여 계절 및 토성에 따른 총 80개의 회귀식을 산정하였다. 관측 토양수분과 모의 토양수분을 비교한 결과 $R^2$가 0.70 (철원), 0.90 (춘천), 0.85 (수원), 0.65 (서산), 0.78 (청주), 0.82 (전주), 0.62 (순천), 0.63 (진주), 0.78 (보성)로 높은 상관성을 보였다. 본 연구에서는 다중분위회귀 모형의 성능을 검증하기 위해 기존의 다중선형회귀모형의 결과와 비교하여 크게 개선됨을 나타냈다.