• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.34 no.1
• /
• pp.117-133
• /
• 2014

In this study, we analysed impacts of the recent increasing trend of exceedance rainfall thresholds for separation of data set and different research periods using Quantile Regression (QR) approach. And also we performed significant test for time series data using linear regression, Mann-Kendall test and Sen test over the Korean major 8-city. Spring and summer precipitation was tend to significant increase, fall and winter precipitation was tend to decrease, and heavy rainy days in last 30 years have increased from 3.1 to 15 percent average. In addition, according to the annual ranking of rainfall occurs Top $10^{th}$ percentile of precipitation for 3IQR (inter quartile range) of the increasing trend, most of the precipitation at the point of increasing trend was confirmed. Quantile 90% percentile of the average rainfall 43.5mm, the increasing trend 0.1412mm/yr, Quantile 99% percentile of the average rainfall 68.0mm, the increasing trend in the 0.1314mm/yr were analyzed. The results can be used to analyze the recent increasing trend for the annual maximum value series information and the threshold extreme hydrologic information. And also can be used as a basis data for hydraulic structures design on reflect recent changes in climate characteristics.

• Journal of vocational education research
• /
• v.37 no.4
• /
• pp.45-66
• /
• 2018

The purpose of this study is to explore the factors affecting the social capital of youth and to draw implications for the policies related to development of the social capital of them. To this end, we utilized the OLS regression model and the quantile regression model exploiting the 12th year dataset of the Korean Education & Employment Panel(KEEP). First, this study shows that the effect on trust is higher than that of the counterpart when the case is a) unmarried, b) with the high level of education, c) with a large asset, d) with high self-respect and the satisfaction for financial situation, and e) social media user. On the other hand, the higher the monthly average income, the lower the trust level. In addition, when the cases are grouped into 25 quantile, 50 quantile, and 75 quantile according to the level of trust, it is revealed empirically that the factors affecting social capital formation are somewhat different. Second, this study also shows that the effect is higher in a specific condition. The effect is higher compared to the counterpart when the case is a) male, b) with children, c) metropolitan city resident, d) non-employee, e) with a large asset, f) with high level of happiness, g) with high expense of purchasing books, and h) social media user. As a result, it is found that there are no personal characteristics that have statistically significant influence on students belonging to the 25th quantile of social capital. This study suggests that, in order to support the formation of social capital of Korean youths, it is necessary to enhance their psychological satisfaction and to provide cultural support or policies. In addition, it suggests that a tailored social capital accumulation program is needed according to the level of social capital, and the support for this need to be changed according to the amount of social capital of young people.

• Journal of the Korean Regional Science Association
• /
• v.31 no.3
• /
• pp.3-17
• /
• 2015

In Korea, the private education spending of the households accounted for about 3% of GDP and such a education fever has been associated with the financial burden of households. The main purpose of this paper is to investigate the effects of regional education environment on the private education expenditure of the households using the Korean Labor and Income Panel Survey(KLIPS) data. The quantile regression model is used to examine whether the effects of regional education environment such as the degree of education fever differ across the 'quantiles' in the conditional distribution of private education expenditure. The empirical results showed that the amount of private education expenditure is under the influence of the regions where the households reside. In addition, it was found that the private education spending of the households in the upper quantile groups are more likely to be affected by the regional education environments than those in the lower quantile groups.

• Asian Journal of Innovation and Policy
• /
• v.12 no.2
• /
• pp.155-176
• /
• 2023

This paper employs datasets from the Enterprise Survey conducted by the World Bank to examine the relationship between four types of innovation defined by the Oslo Manual (OECD, 2005): product innovation, process innovation, marketing innovation, organization innovation, and the firm performance in the selected developing ASEAN economies. The main objective of this paper is to understand the characteristics of innovation activities at the firm level and how various innovation types affect firm performance. The empirical results from ASEAN manufacturing firms reveal that product innovation positively affects firms' performance, while non-technological innovations are negatively related to the performance of firms. The further employed quantile regression provides more insights into the roles of innovation types on different levels of firm performance: while product and process innovations actively contribute to the small and medium-size firms (below 25^th quantile and median), organizational and marketing innovations negatively affect them. Interestingly, the role of process innovation decreases when firm performance grows.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.7
• /
• pp.27-34
• /
• 2020

The study investigates herding behavior in cryptocurrencies in different situations. This study employs daily returns of major cryptocurrencies listed in CCI30 index and sub-major cryptocurrencies and major stock returns listed in Dow-Jones Industrial Average Index, from 2015 to 2018. Quantile regression method is employed to test the herding effect in market asymmetries, inter-dependency and intra-dependency cases. Findings confirm the presence of herding in cryptocurrency in upper quantiles in bullish and high volatility periods because of overexcitement among investors, which lead to high volume trading. Major cryptocurrencies cause herding in sub-major cryptocurrencies, but it is a unidirectional relation. However, no intra-dependency effect among cryptocurrencies and equity market is observed. Results indicate that in the CKK model herding exists at upper quantile in market that may be due when the market is moving fast, continuously trading, and bullish trend are prevailing. Further analysis confirms this narrative as, at upper quantile, the beta of bullish regime is negative and significant, meaning the main source of market herding is a bullish trend in investment, which increases market turbulence and gives investors opportunity to herd. Also, we found that herding in cryptocurrencies exits in high volatility periods, but this herding mostly depends on market activity, not market movement.

• Communications for Statistical Applications and Methods
• /
• v.8 no.1
• /
• pp.15-27
• /
• 2001

One proposal is made for constructing nonparametric estimator of slope parameters in a regression model under symmetric error distributions. This estimator is based on the use of idea of Johns for estimating the center of the symmetric distribution together with the idea of regression quantiles and regression trimmed mean. This nonparametric estimator and some other L-estimators are studied by Monte Carlo.

• Journal of the Korean Geophysical Society
• /
• v.5 no.2
• /
• pp.131-142
• /
• 2002

Geomagnetic transfer function is generally estimated by choosing transfer to minimize the square sum of differences between observed values. If the error structure sccords to the Gaussian distribution, standard least square(LS) can be the estimation. However, for non-Gaussian error distribution, the LS estimation can be severely biased and distorted. In this paper, the Gaussian error assumption was tested by Q-Q(Quantile-Quantile) plot which provided information of real error structure. Therefore, robust estimation such as regression M-estimate that does not allow a few bad points to dominate the estimate was applied for error structure with non-Gaussian distribution. The results indicate that the performance of robust estimation is similar to the one of LS estimation for Gaussian error distribution, whereas the robust estimation yields more reliable and smooth transfer function estimates than standard LS for non-Gaussian error distribution.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2017.05a
• /
• pp.228-232
• /
• 2017

Extreme hydrological events can cause serious threats to the society. Hence, the selection of probability distributions for extreme rainfall is a fundamental issue. For this reason, this study was focused on understanding possible distributional changes in annual daily maximum rainfalls (AMRs) over time in Sri Lanka using quantile regression. A simplified nine-category distributional-change scheme based on comparing empirical probability density function of two years (i.e. the first year and the last year), was used to determine the distributional changes in AMRs. Daily rainfall series of 13 station over Sri Lanka were analyzed for the period of 1960-2015. 4 distributional change categories were identified for the AMRs. 5 stations showed an upward trend in all the quantiles (i.e. 9 quantiles: from 0.05 to 0.95 with an increment of 0.01 for the AMR) which could give high probability of extreme rainfall. On the other hand, 8 stations showed a downward trend in all the quantiles which could lead to high probability of the low rainfall. Further, we identified a considerable spatial diversity in distributional changes of AMRs over Sri Lanka.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.11
• /
• pp.79-86
• /
• 2021

In recent years, firm performance has been a topic that attracts many researchers. It is extremely important to identify the factors that change firm performance. In the current trend of competition and integration, foreign ownership, product market competition is found to reduce agency costs and impact firm performance. The purpose of this research is to investigate the relationship between foreign ownership, product market competition, and firm performance. Our research using a quantile regression model, through panel data of 290 companies listed on the Vietnam stock exchange (include Ho Chi Minh and Hanoi stock exchanges) from 2017 to 2019 that was collected by Thomson - Reuters DataStream has shown that foreign ownership and product market competition have a positive impact on Tobin's Q but are not statistically significant with ROA. Critically, our quantile regression results suppose foreign ownership, product market competition have a significantly larger positive impact in high-performing firms relative to low-performing firms. The results help propose solutions to planners and managers to change foreign ownership and product market competition to increase business performance. Besides, through quantile regression analysis, managers need to pay attention to the impact on foreign ownership, product market competition; there will be a difference between high-performing firms relative to low-performing firms.

• Journal of Preventive Medicine and Public Health
• /
• v.56 no.6
• /
• pp.515-522
• /
• 2023

Objectives: The pandemic caused by coronavirus disease 2019 (COVID-19) has exerted an unprecedented impact on the health of populations worldwide. However, the adverse health consequences of the pandemic in terms of infection and mortality rates have varied across countries. In this study, we investigate whether COVID-19 mortality rates across a group of developed nations are associated with characteristics of their healthcare systems, beyond the differential policy responses in those countries. Methods: To achieve the study objective, we distinguished healthcare systems based on the extent of healthcare decommodification. Using available daily data from 2020, 2021, and 2022, we applied quantile regression with non-additive fixed effects to estimate mortality rates across quantiles. Our analysis began prior to vaccine development (in 2020) and continued after the vaccines were introduced (throughout 2021 and part of 2022). Results: The findings indicate that higher testing rates, coupled with more stringent containment and public health measures, had a significant negative impact on the death rate in both pre-vaccination and post-vaccination models. The data from the post-vaccination model demonstrate that higher vaccination rates were associated with significant decreases in fatalities. Additionally, our research indicates that countries with healthcare systems characterized by high and medium levels of decommodification experienced lower mortality rates than those with healthcare systems involving low decommodification. Conclusions: The results of this study indicate that stronger public health infrastructure and more inclusive social protections have mitigated the severity of the pandemic's adverse health impacts, more so than emergency containment measures and social restrictions.