• KDI Journal of Economic Policy
• /
• v.39 no.3
• /
• pp.1-18
• /
• 2017

The anchoring effect can be found when a decision shows cognitive prejudice towards the initial information given. Several studies have argued that such an effect is present even for judges in the courtroom. This paper seeks to find a relationship between judges' decisions on penalty sentences and the sentences recommended by prosecutors. In this study, 2,773 actual court cases are considered in the analysis, and quantile regression is used to show that the sentencing decisions judges make are anchored by the recommendations of prosecutors. However, this reliance on recommendations differs according to the seriousness of the crime committed. Specifically, at the lowest penalty levels, a one-month increase in the prosecutors' sentencing recommendation results in a 0.25-month increase in the judges' sentence, while at the highest sentence level, the judges' sentences increase by 0.78 months under an identical condition. The results of this research indicate the need to create more objective and clear sentencing guidelines in the future in an effort to mitigate the psychological pressure experienced by judges with regard to serious offences or heinous crimes.

• KDI Journal of Economic Policy
• /
• v.43 no.2
• /
• pp.1-22
• /
• 2021

The effects of social distancing measures on income distributions and aggregate variables are examined with an off-the-shelf heterogeneous-agent incomplete-market model. The model shows that social distancing measures, which limit households' labor supply, can decrease the labor supply of low-income households who hold insufficient assets and need income the most given their borrowing constraints. Social distancing measures can therefore exacerbate income inequality by lowering the incomes of the poor. An equilibrium interest rate can fall when the social distancing shock is expected to be persistent because households save more to prepare for rising consumption volatility given the possibility of binding to the labor supply constraint over time. When the shock is expected to be transitory, in contrast, the interest rate can rise upon the arrival of the shock because constrained households choose to borrow more to smooth consumption given the expectation that the shock will fade away. The model also shows that social distancing shocks, which diminish households' consumption demand, can decrease households' incomes evenly for every income quantile, having a limited impact on income inequality.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.24 no.4
• /
• pp.201-217
• /
• 2022

The United States is one of the largest producers of major crops such as wheat, maize, and soybeans, and is a major exporter of these crops. Therefore, it is important to estimate the crop production of the country in advance based on reliable long- term weather forecast information for stable crops supply and demand in Korea. The purpose of this study is to improve the seasonal predictability of the agro-climatic indices over the United States by using regional-scale daily temperature. For long-term numerical weather prediction, a dynamical downscaling is performed using Weather Research and Forecasting (WRF) model, a regional climate model. As the initial and lateral boundary conditions of WRF, the global hourly prediction data obtained from the Pusan National University Coupled General Circulation Model (PNU CGCM) are used. The integration of WRF is performed for 22 years (2000-2021) for period from June to December of each year. The empirical quantile mapping, one of the bias correction methods, is applied to the timeseries of downscaled daily mean, minimum, and maximum temperature to correct the model biases. The uncorrected and corrected datasets are referred WRF_UC and WRF_C, respectively in this study. The daily minimum (maximum) temperature obtained from WRF_UC presents warm (cold) biases over most of the United States, which can be attributed to the underestimated the low (high) temperature range. The results show that WRF_C simulates closer to the observed temperature than WRF_UC, which lead to improve the long- term predictability of the temperature- based agro-climatic indices.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.57 no.5
• /
• pp.1-12
• /
• 2015

The study aimed to project inflows and demmands for the agricultural reservoir watersheds in South Korea considering a variety of regional characteristics and the uncertainty of future climate information. The study bias-corrected and spatially downscaled retrospective daily Global Climate Model (GCM) outputs under Representative Concentration Pathways (RCP) 4.5 and 8.5 emission scenarios using non-parametric quantile mapping method to force Soil and Water Assessment Tool (SWAT) model. Using the historical simulation, the skills of un-calibrated SWAT model (without calibration process) was evaluated for 5 reservoir watersheds (selected as well-monitored representatives). The study then, evaluated the performance of 9 GCMs in reproducing historical upstream inflow and irrigation demand at the five representative reservoirs. Finally future inflows and demands for 58 watersheds were projected using 9 GCMs projections under the two RCP scenarios. We demonstrated that (1) un-calibrated SWAT model is likely applicable to agricultural watershed, (2) the uncertainty of future climate information from different GCMs is significant, (3) multi-model ensemble (MME) shows comparatively resonable skills in reproducing water balances over the study area. The results of projection under the RCP 4.5 and RCP 8.5 scenario generally showed the increase of inflow by 9.4% and 10.8% and demand by 1.4% and 1.7%, respectively. More importantly, the results for different seasons and reservoirs varied considerably in the impacts of climate change.

• Journal of Korean Society on Water Environment
• /
• v.35 no.2
• /
• pp.131-144
• /
• 2019

Climate Change affects the hydrological cycle in agricultural watersheds through rising air temperature and changing rainfall patterns. Agricultural watersheds in Korea are characterized by extensive paddy fields and intensive water use, a resource that is under stress from the changing climate. This study analyzed the effects of climate change on river flows for Geum Cheon and Eun-San Choen watershed using STREAM, a semi-distributed watershed model. In order to evaluate the performance and improve the reliability of the model, calibration and validation of the model was done for one flow observation point and three reservoir water storage ratio points. Climate change scenarios were based on RCP data provided by the Korea Meteorological Administration (KMA) and bias corrections were done using the Quantile Mapping method to minimize the uncertainties in the results produced by the climate model to the local scale. Because of water mass-balance, evapotranspiration tended to increase steadily with an increase in air temperature, while the increase in RCP 8.5 scenario resulted in higher RCP 4.5 scenario. The increase in evapotranspiration led to a decrease in the river flow, particularly the decrease in the surface runoff. In the paddy agricultural watershed, irrigation water demand is expected to increase despite an increase in rainfall owing to the high evapotranspiration rates occasioned by climate change.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.1
• /
• pp.237-246
• /
• 2021

This paper explores the relationship between price mechanism and flipping activity of initial public offerings (IPOs) in Pakistan's emerging economy. This study uses a cross-sectional data set of 95 firms listed on Pakistan Stock Exchange from 2000 to 2019. This study employs the ordinary least square and quantile regression techniques to capture the relationship between price mechanism and flipping activity. The results show that book-built IPOs flip substantially less than fixed-price IPOs. This is consistent with the signaling theory assertion that roadshows are arranged by underwriters to capture investors' demand and set the offer prices of IPOs. If investors learn the fair values of quality IPOs, then the offer prices will be close to the intrinsic values, thus reducing flipping. The findings also provide conclusive evidence for understanding the usefulness of and the more relevant information regarding the pricing mechanism. In particular, it provides a better understanding of how companies actually use the pricing mechanism information in the flipping of IPO shares. The results of this study are also valuable to underwriters, and regulators, for instance, provides underwriters with the discretion to allocate the IPO shares and the SECP, in revising regulation on the disclosure of IPO pricing methods.

• Information Systems Review
• /
• v.24 no.2
• /
• pp.1-20
• /
• 2022

Researchers are making contradictory claims through the concept of superstars and long tails about how the development of IT technology affects demand distribution. Unlike previous studies that focused on changes in demand from a macro point of view, this study explored whether the relationship between a company's marketing activities and consumer response differs depending on the product location (i.e., superstar vs. long tail) from a micro point of view. Based on the marketing mix framework, hypotheses were developed based on the relevant literature. In the case of empirical analysis, 2,835 daily data from 63 Korean films were tested using the quantile regression method. As a result of the analysis, it was found that the influence of marketing mix factors on sales varies depending on the location of the product. Specifically, the appeal breadth of the film and the effect of owned media are enhanced in superstar products, and the effect of acquisition media in long-tail products is enhanced and the negative effects of competition are mitigated. Unlike previous studies that focused on macroscopic changes in demand distribution, this study suggested marketing activities suitable for practitioners through microscopic analysis.