• KDI Journal of Economic Policy
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• v.44 no.4
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• pp.43-78
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• 2022

The arena of strategic competition between the US and China is expandable from international politics, trade and commerce to finance. What would happen if financial sanctions against China are imposed by the US? Would US financial sanctions lead to a sudden outflow of foreign capital and a liquidity crisis in China? We try to address these questions by estimating China's capital flows-at-risk with the CDS premium on Chinese sovereign funds. We follow Gelos et al. (2019) in setting up a quantile regression model from which China's foreign capital flow-at-risks are estimated. Based on our analysis of China's monthly capital flow data, we find that a rise in the CDS premium has statistically significant negative impacts on China's foreign capital flows-at-risk, mainly in banking flows. However, the analysis also found that due to favorable global conditions, an increase in the CDS premium is unlikely to trigger a shift to a sudden outflow of foreign capital at the moment. Meanwhile, this study found no statistically significant correlation between Korea's capital flows-at-risk and the CDS premium, suggesting that the negative impact of US financial sanctions on China would not increase the probability of capital flight from Korea in a significant manner.

• Communications of the Korean Mathematical Society
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• v.20 no.1
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• pp.145-159
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• 2005

In this paper we consider the problem of testing statistical hypotheses for unknown parameters in nonlinear regression models and propose three asymptotically equivalent tests based on regression quantiles estimators, which are Wald test, Lagrange Multiplier test and Likelihood Ratio test. We also derive the asymptotic distributions of the three test statistics both under the null hypotheses and under a sequence of local alternatives and verify that the asymptotic relative efficiency of the proposed test statistics with classical test based on least squares depends on the error distributions of the regression models. We give some examples to illustrate that the test based on the regression quantiles estimators performs better than the test based on the least squares estimators of the least absolute deviation estimators when the disturbance has asymmetric and heavy-tailed distribution.

• Journal of the Korean Data and Information Science Society
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• v.11 no.2
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• pp.235-245
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• 2000

In this paper, we consider the Regression Quantiles Estimators in nonlinear regression models. This paper provides the sufficient conditions for strong consistency and asymptotic normality of proposed estimation and drives asymptotic relative efficiency of proposed estimatiors with least square estimation. We give some examples and results of Monte Carlo simulation to compare least square and regression quantile estimators.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.7
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• pp.1025-1031
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• 2017

This study compares the characteristics and the determinants of household electricity consumption for low electricity consuming and high electricity consuming households. The data are drawn from a household energy consumption sample survey by Korea Energy Economics Institute in 2015. The results show the differences in socio-demographic, dwelling, and electricity consumption characteristics between two households. Next, the factors affecting the household's electricity consumption are investigated. Common factor affecting the electricity consumption function is only the number of electrical appliances. There are also the differences in major determinants of the household's electricity consumption functions for two households. The results of this study would be useful for understanding socio-demographic, dwelling, and electricity consumption characteristics of low electricity consuming and high electricity consuming households.

• 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.

• Journal of applied mathematics & informatics
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• v.27 no.1_2
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• pp.315-326
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• 2009

The unknown parameters in regression models are usually estimated by using various existing methods. There are several existing methods, such as the least squares method, which is the most common one, the least absolute deviation method, the regression quantile method, and the asymmetric least squares method. For the nonlinear time series regression models, which do not satisfy the general conditions, we will compare them in two ways: 1) a theoretical comparison in the asymptotic sense and 2) an empirical comparison using Monte Carlo simulation for a small sample size.

• Management & Information Systems Review
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• v.32 no.1
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• pp.173-194
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• 2013

The purpose of this study drew the core elements of ISO26000 by analyzing the elements suitable to the characteristics of casino companies, and examined the influence of the core elements of ISO26000 on organizational trust following the level of organizational trust of employees. As a result of the factor analysis, among the 7 measurement items of ISO26000, improvement of governance and fair operating practices were simplified into one factor and thus 6 factors were used for empirical analysis. Therefore, multiple regression analysis using least square method was conducted to examine the impacts of the 6 elements. As a result, 5 variables excluding human rights had significant impacts on the organizational trust. Concretely, the 5 core elements of ISO26000 (labor practices, governance and fair operation, consumer issues, environment and community social and economic development) had significant impact on organization trust in order. In addition, the results of quantile regression analysis show the core elements of ISO26000 had different impacts on organizational trust depending on the level of organizational trust of employees.

• Communications for Statistical Applications and Methods
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• v.28 no.6
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• pp.627-641
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• 2021

An asymmetric least squares estimation method has been employed to estimate linear models for percentile regression. An asymmetric maximum likelihood estimation (AMLE) has been developed for the estimation of Poisson percentile linear models. In this study, we propose generalized nonlinear percentile regression using the AMLE, and the use of the parametric bootstrap method to obtain confidence intervals for the estimates of parameters of interest and smoothing functions of estimates. We consider three conditional distributions of response variables given covariates such as normal, exponential, and Poisson for three mean functions with one linear and two nonlinear models in the simulation studies. The proposed method provides reasonable estimates and confidence interval estimates of parameters, and comparable Monte Carlo asymptotic performance along with the sample size and quantiles. We illustrate applications of the proposed method using real-life data from chemical and radiation epidemiological studies.

• Journal of Korea Technology Innovation Society
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• v.18 no.1
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• pp.1-27
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• 2015

Korea has increased R&D investment continuously for the improvement of global technological competencies. Korea ranked first in the world with 4.15 percent in the ratio of R&D investment to GDP. In particular, the private sector occupies a crucial position of technological innovations in Korea, constituting 78.5% of total R&D investment. However, quantitative growth strategy is no longer effective, so efforts to enhance efficiency by upgrading qualitative level are badly needed. This paper studied methods for improving firms' business performance. For this, it tried to empirically verify technology strategy and technology planning capability's influence factors on the improvement of business performance. The study showed that technology strategy and technology planning activities have positive effects on the improvement of business performance. And it was revealed that coordination flexibility contributes to the enhancement of business performance by positively controlling technology planning activities. The study performed sample survey on the companies with R&D centers and multiple regression analysis and quantile regression were used for the analysis.

• 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.