• The Journal of Industrial Distribution & Business
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• v.9 no.5
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• pp.63-72
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• 2018

Purpose - This work analyzes, in detail, the specification of vector error correction model (VECM) and thus examines the relationships and impact among seven economic variables for USA - balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), a measure of the money supply that includes total currency as well as large time deposits, institutional money market funds, short-term repurchase agreements and other larger liquid assets (M3), real rate of interest (IR_REAL) and household credits (LOAN). In particular, we search for the main explanatory variables that have an effect on stock and real estate market, respectively and investigate the causal and dynamic associations between them. Research design, data, and methodology - We perform the time series vector error correction model to infer the dynamic relationships among seven variables above. This work employs the conventional augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root techniques to test for stationarity among seven variables under consideration, and Johansen cointegration test to specify the order or the number of cointegration relationship. Granger causality test is exploited to inspect for causal relationship and, at the same time, impulse response function and variance decomposition analysis are checked for both short-run and long-run association among the seven variables by EViews 9.0. The underlying model was analyzed by using 108 realizations from Q1 1990 to Q4 2016 for USA. Results - The results show that all the seven variables for USA have one unit root and they are cointegrated with at most five and three cointegrating equation for USA. The vector error correction model expresses a long-run relationship among variables. Both IR_REAL and M3 may influence real estate market, and GDP does stock market in USA. On the other hand, GDP, IR_REAL, M3, STOCK and LOAN may be considered as causal factors to affect real estate market. Conclusions - The findings indicate that both stock market and real estate market can be modelled as vector error correction specification for USA. In addition, we can detect causal relationships among variables and compare dynamic differences between countries in terms of stock market and real estate market.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.1
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• pp.75-83
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• 2020

This study investigated the effects of El Niño and La Niña on coastal upwelling in the East Sea of Korea using long-term (1967-2017) water temperature observation data and Oceanic Niño Index (ONI). As a result of time series analysis of water temperature, the occurrence frequency of summer coastal upwelling was the highest in the southeastern (Ulgi ~ Gimpo) coast. In 1987-1988 and 1997-1998, when the annual fluctuations of ONI plunged more than 2.5, the water temperature in whole coast areas of the East Sea (Busan ~ Goseung) rose by 4 ~ 7 ℃. The temperature structure of the East Sea coastal water was different when El Niño was strong with ONI above 1.5 and La Niña with strong ONI below -0.8. When El Niño is strong, the water temperature anomaly in coastal waters is negative. This is due to the strong baroclinic tilting and the formation of shallow temperature stratification in the coastal waters. The strong La Niña season is opposite to the strong El Niño season, whereas the water temperature anomaly is positive. In addition, the baroclinic tilting is weaker than the time of strong El Niño and the temperature stratification is formed deeper than the time of strong El Niño. The formation of temperature stratification at shallow depths when El Niño is strong can increase the probability of occurrence coastal upwelling caused by southerly winds in the summer season. On the contrary, when La Niña is strong, occurrence of coastal upwelling is less likely even if the southerly wind blows continuously. This is because the temperature stratification is formed at deeper than when El Niño is strong.

• Proceedings of the KIEE Conference
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• 2004.11d
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• pp.93-96
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• 2004

In this paper, we analyzed the current limiting characteristics according to increase of source voltage in the flux-lock type high-Tc superconducting fault current limiter (SFCL). The flux-lock type SFCL consisted of two coils, which were wound in parallel each other through an iron core, and high-Tc superconducting (HTSC) element connected with coil 2 in series. The flux-lock type SFCL has the characteristics better in comparison with the resistive type SFCL because the fault current in the flux-lock type SFCL can be divided into two coils by the inductance ratio of coil 1 and coil 2. The fault current limiting operation of the flux-lock type SFCL can be different due to winding direction of the two coils. The winding method where the decrease of linkage flux between two coils in the accident happens is called the subtractive polarity winding and the winding method in case of the increase of linkage flux is called the additive polarity winding. The fault current limiting experiments according to the source voltage were performed for these two winding methods. Through the comparison and the analysis of the experimental data, we confirmed that the quench time was shorter, irrespective of the winding direction as the source voltage increased and that the fault current and the HTSC's resistance increased as the amplitude of the source voltage increased. The additive polarity winding made the fast quench time and the lower resistance of HTSC element in comparison with the subtractive polarity winding. The fault current of the subtractive polarity winding was larger than that of the additive polarity winding. In conclusion, we found that the additive polarity winding reduced the burden of SFCL because the quench time was shorter and the fault current was smaller than those of the subtractive polarity winding.

• Journal of Korea Port Economic Association
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• v.32 no.4
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• pp.165-182
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• 2016

This study examines the competitiveness and cooperativeness among the container ports in East Asia by analyzing their monthly dynamics in eight years (2008-2015). Time series data on container throughput divided into origin and destination (O/D), such as the top six Chinese ports and the transshipment (T/S) ports such as Hong Kong, Busan, and Singapore, are computed with two methods based on the Vector Error Correction Model (VECM). The first Granger causality test results show that Busan T/S has significant bilateral relations with three Chinese O/D ports; and significant unidirectional relations with three other O/D ports. Shenzhen port has significant bilateral relations with Singapore, and has a significant unidirectional relation with Hong Kong port. Co-integrating test results showed that Busan holds negative co-integration with all Chinese O/D ports. Impulse response function (IRF) results show an opposite direction between paired ports. The ratios of the impulse from T/S ports are significantly high to one another in the short-run, but its power declines as time passes. The ratio of the impulse from the Chinese ports to T/S ports is less significant in the short-run period, however, it becomes more significant as time passes. The significance of most shocks was high in the second period, but was diluted after the sixth period.

• Economic and Environmental Geology
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• v.29 no.6
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• pp.699-712
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• 1996

Field scale experiments using an automated 144-channel TDR system were conducted which monitored the movement of solute through unsaturated loamy soils. The experiments were carried out on two different field plots of 0.54 ha to study the vertical movement of solute plume created by applying a square pulse of $CaCl_2$ as a tracer. The residence concentration was monitored at 24 locations on a transect and 5 depths per location by horizontally-positioning 50 cm long triple wire TDR probes to study the heterogeneity of solute travel times and the governing transport concept at field scale. This paper describes details of experimental methodology and calibration aspects of the TDR system. Three different calibration methods for estimation of solute concentration from TDR-measured bulk soil electrical conductivity were used for each field site. Data analysis of mean breakthrough curves (BTCs) and parameters estimated using the convection-dispersion model (CDE) and the convective-lognormal transfer function model (CLT) reveals that the automated TDR system is a viable technique to study the field scale solute transport providing a normal distribution of resident concentration in a high resolution of time series, and that calibration method does not significantly affect both the shape of BTC and the parameters related to the peak travel time. Among the calibration methods, the simple linear model (SLM), a modified version of Rhoades' model, appears to be promising in the calibration of horizontally-positioned TDR probes at field condition.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.1
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• pp.55-73
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• 2024

Unicorn companies are attracting attention around the world as they are recognized for their high corporate value in a short period of time as an innovative business models. Their growth process presents good lessons for the startup ecosystem and have a positive impact on national economic development and job creation. However, previous studies related to unicorn companies are focused on 'event studies' and 'case studies' such as characteristics of founders, environmental factors, business models and success/failure cases of companies already recognized as unicorns rather than a multifaceted approach. The occurrence of unicorn companies and Macroscopic analysis of related factors is lacking. Against this background, this study are considering the characteristics of unicorns examined through previous research and the current status unicorns with a high proportion of technology companies, the purpose was to analyze the impact of the country's technological competitiveness, such as 'technology human resource index', 'R&D index', and 'technology infrastructure index', on the increase in unicorn companies. For statistical analysis, data published by various international organizations, the Bank of Korea, and Statistics Korea from 2017 to 2020 and unicorn company data compiled by CB Insights were used as panel data for 44 countries to be tested by multiple regression analysis. As a result of the study, it was confirmed that the number of science majors had a positive (+) effect on the increase of unicorn companies in the case of technology human resource index, and in the case of R&D index, the total amount of R&D investment had a positive (+) effect on the increase of unicorn companies, while the number of Triad Patents Families and the number of scientific and technological papers published had a negative (-) effect on the increase of unicorn companies. Finally, in the case of technology infrastructure index, it was confirmed that the number of the world's 500th-ranked universities had a positive (+) effect on the increase of unicorn companies. This study is the first to reveal the causal relationship between national technological competitiveness and unicorn company growth based on country-specific and time-series empirical data, which were insufficiently covered in previous studies. and compared to the UN's ranking of the global industrial competitiveness index and the OECD's total R&D investment by country, Korea is considered to have technological and growth potential, while the number of unicorn companies driving growth as leaders of the innovative economy is relatively small, so the research results can be used when establishing policies to discover and foster unicorn companies in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.668-678
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• 2017

In this study, the hydrological and meteorological drought index with precipitation as a major factor were calculated, and various analyses of hydrological drought were conducted. The Modified Surface Water Supply Index (MSWSI) was applied to the hydrological drought index and Standardize Precipitation Index (SPI) was used to estimate the meteorological drought index. The target area for the estimation is the dam area among MSWSI categories. The 4001 basin with 43 years data from 1975 to 2017 was analyzed for the drought occurrence status and time series plotted with the monthly SPI and MSWSI. For the dam watershed based on the precipitation that has the role of a water supply in the hydrological cycle, correlation analysis of precipitation, dam inflow, and stream flow was performed by the monthly and moving average (2~9 months), and the correlation between meteorological and hydrological index by monthly and moving average (3, 6 months) was then calculated. The result of multifaced analysis of the hydrological drought index and meteorological drought index is believed to be useful in developing water policy.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.511-524
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• 2017

This study aims to evaluate the availability of ABM (Active-Based Model), FEATHERS, as a policy evaluation tool. To achieve the goal, scenario analysis on flexible working policy was conducted to measure its impact on activity-travel behavior. As a consequence, there seems no significant change in worker's daily life, other than mitigating traffic congestion due to decreasing commuting travel in the rush hour. The result of VKT (vehicle kilometers traveled) shows an opposite pattern according to given household/individual constraints. The scenario analysis on telecommuting indicates a decreasing trend in both travel frequency and distance because of the diminished number of commuting trips. As the activity space of telecommuters is shifted to a residential area, there are more short-distance trips by using non-motorized transport, which leads to decrease in VKT (using a private vehicle). Thus, the sensitivity of VKT by population groups varies due to transport mode shift (between personal and another mode) and growing non-work trips (using a private mode). This study found few things. First, it is necessary to evaluate the details of policy impact by population groups since it can be varied depending on household/individual characteristics. Second, the case study shows a promising performance of ABM as policy measurement that provides reality in policy evaluation. Third, ABM allows us to do more accurate analysis (i.e. time-series analysis by population groups) of policy assessment than those of FSM (Four-Step Model). Lastly, a further effort in data collection, literature review, and expert survey should be made to enhance the accuracy and confidence of future research.

• Journal of the Korean earth science society
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• v.40 no.6
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• pp.613-623
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• 2019

Over the past decades, daily sea surface temperature (SST) composite data have been produced using periodically and extensively observed satellite SST data, and have been used for a variety of purposes, including climate change monitoring and oceanic and atmospheric forecasting. In this study, we evaluated the accuracy and analyzed the error characteristic of the SST composite data in the sea around the Korean Peninsula for optimal utilization in the regional seas. We evaluated the four types of multi-satellite SST composite data including OSTIA (Operational Sea Surface Temperature and Sea Ice Analysis), OISST (Optimum Interpolation Sea Surface Temperature), CMC (Canadian Meteorological Centre) SST, and MURSST (Multi-scale Ultra-high Resolution Sea Surface Temperature) collected from January 2016 to December 2016 by using in-situ temperature data measured from the Ieodo Ocean Research Station (IORS). Each SST composite data showed biases of the minimum of 0.12℃ (OISST) and the maximum of 0.55℃ (MURSST) and root mean square errors (RMSE) of the minimum of 0.77℃ (CMC SST) and the maximum of 0.96℃ (MURSST) for the in-situ temperature measurements from the IORS. Inter-comparison between the SST composite fields exhibited biases of -0.38-0.38℃ and RMSE of 0.55-0.82℃. The OSTIA and CMC SST data showed the smallest error while the OISST and MURSST data showed the most obvious error. The results of comparing time series by extracting the SST data at the closest point to the IORS showed that there was an apparent seasonal variation not only in the in-situ temperature from the IORS but also in all the SST composite data. In spring, however, SST composite data tended to be overestimated compared to the in-situ temperature observed from the IORS.

• Economic and Environmental Geology
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• v.34 no.4
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• pp.375-383
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• 2001

We extracted sea surface heights(SSH) from the TopexJPoseidon(T/P) radar altimeter data to compare with fhe SSH estimated from in-situ lide gauges(T/G) at Ulleungdo, Pohang, and SockcholMucko sites. Selection criteria such as wet/dry troposphere, ionosphere, and ocean tide were used to estimate accurate SSH. For time series analysis, the one-hour interval tide gauge SSHs were resampled al lO-day interval of the satellite SSHs. The ocean tide model applied in the altimeter data processing showed periodic aliasings of 175.5 day, 87.8 day, 62J day, 58.5 day, 49.5 day and 46.0 day, and, hence, the ZOO-day filtering was applied to reduce these spectral noises. Wavenumber correlation analysis was also applied to extract common components between the two SSHs, resulting in enhancing the correlation coefficient(CC) dramatically. The original CCs between the satenite and tide gauge SSHs are 0.46. 0.26, and 0.]5, respectively. Ulleungdo shows the largest cc bec;luase the site is far from the coast resulting in the minimun error in the satellite observations. The CCs were then increased to 0.59, 030, and 0.30, respectively, after 200.day filtering, and to 0.69, 0.63. and 0.59 after removing inversely correlative components using wavenumber correlation analysis. The CCs were greatly increased by 87, 227, and 460% when the wavenumber correlation analysis was followed by 2oo-day filtering, resulting in the final CCs of 0.86, 0.85, 0.84, respectively. It was found that the best SSHs were estimated when the two methods were applied to the original data. The low-pass filtered TIP SSHs were found to be well correlated with the TIG SSHs from tide gauges, and the best correlation results were found when we applied both low-pass filtering and spectral correlation analysis to the original SSHs.