Journal of the Economic Geographical Society of Korea
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v.25
no.1
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pp.147-170
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2022
This article analyzes the spillover effects by dividing the weekly rate of return on apartment prices in 70 si-gun-gu (local area) in the Capital Region into three periods: the entire period (April 2008~August 2021); the period before the price surge (April 2008~October 2018); and the period of price surge (November, 2018~August 2021), based on a consideration of the cycle of fluctuations in apartment sales prices and the timing of the current government's policy interventions. The results obtained from this analysis are summarized as follows. First, the analysis of the spillover effects is similar to or different from the results of existing work depending on the period. The analysis of the spillover effects on the entire period and the period before the price surge shows that the 'Gangnam' effect exists in the apartment market in the Capital Region. On the other hand, the analysis of the spillover effects on the period of price surge reveals different results than before. The spillover effect index calculated through the analysis of the rolling sample decreases during the decline in the cycle of apartment sales prices, while the opposite trend is shown during the upward period. Looking at the timing between the peak of the spillover effect index and policy interventions, it appears that the government's policy interventions took place after the peak of the spillover effect index in 2017, before the peak in 2018 and 2019, and around or after the peak after 2020.
Journal of the Korean Data and Information Science Society
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v.25
no.6
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pp.1361-1369
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2014
This research is for analyzing the change rate of housing rent price index produced by KAB (Korea Appraisal Board) in the monthly periodical, Survey on Housing Monthly Rent. The index is a very important and useful indicator to understand and diagnose the house rental market. However, the index is criticized in that it tends to decline when the price level of Jeonse (i.e., a typical type of dwellings in Korea, generally leased on a deposit basis for 1 or 2 years) is highly going up, which is inconsistent with the actual economic sentiment of tenants. We verify the reason why such phenomenon occurs and suggest a simple but novel method to analyze properly the change rate of the index. The main findings are as follows. The key factor to trigger the problem is the use of the conversion rate for Jeonse-to-monthly rent for constructing the rent price indexes. We separate the effect of the conversion rate out of the change rate of the index and quantify the adjusted real change rate showing an increase of the rent price level which is masked by the conversion rate before.
This paper analyzes the macroeconomic effects of elections on the Korean economy and their future ramifications. It measures the shocks to the Korean economy caused by elections by taking the average of sample forecast errors from four major elections held in the 1980s. The seven variables' Bayesian Vector Autoregression Model which includes the Monetary Base, Industrial Production, Consumption, Consumer Price, Exports, and Investment is based on the quarterly time series data starting from 1970 and is updated every quarter before forecasts are made for the next quarter. Because of this updating of coefficients, which reflects in part the rapid structural changes of the Korean economy, this study can capture the shock effect of elections, which is not possible when using election dummies with a fixed coefficient model. In past elections, especially the elections held in the 1980s, $M_2$ did not show any particular movement, but the currency and base money increased during the quarter of the election was held and the increment was partly recalled in the next quarter. The liquidity of interest rates as measured by corporate bond yields fell during the quarter the election and then rose in the following quarter, which is somewhat contrary to the general concern that interest rates will increase during election periods. Manufacturing employment fell in the quarter of the election because workers turned into campaigners. This decline in employment combined with voting holiday produce a sizeable decline in industrial production during the quarter in which elections are held, but production catches up in the next quarter and sometimes more than offsets the disruption caused during the election quarter. The major shocks to price occur in the previous quarter, reflecting the expectational effect and the relaxation of government price control before the election when we simulate the impulse responses of the VAR model, imposing the same shocks that was measured in the past elections for each election to be held in 1992 and assuming that the elections in 1992 will affect the economy in the same manner as in the 1980s elections, 1992 is expected to see a sizeable increase in monetary base due to election and prices increase pressure will be amplified substantially. On the other hand, the consumption increase due to election is expected to be relatively small and the production will not decrease. Despite increased liquidity, a large portion of liquidity in circulation being used as election funds will distort the flow of funds and aggravate the fund shortage causing investments in plant and equipment and construction activities to stagnate. These effects will be greatly amplified if elections for the head of local government are going to be held this year. If mayoral and gubernatorial elections are held after National Assembly elections, their effect on prices and investment will be approximately double what they normally will have been have only congressional and presidential elections been held. Even when mayoral and gubernatorial elections are held at the same time as congressional elections, the elections of local government heads are shown to add substantial effects to the economy for the year. The above results are based on the assumption that this year's elections will shock the economy in the same manner as in past elections. However, elections in consecutive quarters do not give the economy a chance to pause and recuperate from past elections. This year's elections may have greater effects on prices and production than shown in the model's simulations because campaigners' return to industry may be delayed. Therefore, we may not see a rapid recall of money after elections. In view of the surge in the monetary base and price escalation in the periods before and after elections, economic management in 1992 should place its first priority on controlling the monetary aggregate, in particular, stabilizing the growth of the monetary base.
Journal of the Korean Regional Science Association
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v.35
no.1
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pp.59-72
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2019
This study focused on low fertility and population decline which threaten national competitiveness. Therefore, a comprehensive analysis was attempted on the impact of housing characteristics and residential area characteristics of newlyweds on their birth plan. To this end, the hierarchical linear model(HLM) was implemented using '2016 Korea Newlyweds' Housing Survey' data. The main findings of this study are as follows. First, the birth plan of newlyweds is affected not only by housing characteristics, but also residential area characteristics such as the average housing price, average private education expenses and the number of local child centers. Second, the use of housing loans and the housing tenure have an interaction effect with the average housing price and the number of local child centers among the residential area characteristics. In other words, the use of housing loans has a negative effect on the birth plan if the housing price is high in the area, and being renter household has a positive effect on the birth plan if the number of local child centers is high in the area. These findings suggest that governmental effort to raise the birthrate of newlyweds should take into account their housing characteristics as wells as residential area characteristics.
Purpose - This study provides evidence of the impact of the mandatory adoption of Korean equivalents to International Financial Reporting Standards (K-IFRS) on accounting quality. K-IFRS uses fair value as a basis of measurement and is characterized by principle-based standards. These characteristics can lead to a decrease in conservatism. Therefore, this study aims to examine whether or not there is a change in the level of conservatism before and after the enforcement of K-IFRS (2007~2014). By comparing 2007 through 2008 and 2013 through 2014 (excluding 2009 to 2012), we test "the temporary adjustment phenomenon" and document an overall decline in the degree of conservatism after the adoption of K-IFRS. Research design, data, and methodology - Our sample is comprised of data of all listed Korea Composite Stock Price Index (KOSPI) manufacturing distribution companies in Korea from 2007 to 2014, which yields the pooled sample of 4,412 (panel A) and 1,915 (panel B) firm-year observations for hypotheses 1 and 2. In line with recent literature, we adopt the Givoly and Hayn (2000) model, which recomputes the non-operating accruals, excluding two components that are most likely to capture the effect of restructuring activities: special items and gains or losses from discontinued operations. In addition, we also use these variables: SIZE, LEV, INV_CYCLE, ROA, OWN, and FOR. Results - Our sample period spans 2007 to 2014. This offers evidence on the effect of the mandatory adoption of IFRS on conservatism. Our findings can be summarized as follows. First, in panel A, for mandatory K-IFRS adoption (2011), we do not find any significant evidence of conservatism. We can guess that the "temporary adjustment phenomenon" is the reason that we do not find significant evidence of conservatism. Second, we investigate panel B from 2009 to 2012. We document an overall decline in the degree of conservatism after the adoption of K-IFRS. We can assume that these results are due to "the temporary adjustment phenomenon." Conclusions - This study finds that conservatism significantly decreased after IFRS adoption. In particular, this study makes the initial effort to elucidate "the temporary adjustment phenomenon" to analyze the effect of K-IFRS on conservative accounting. We argue that K-IFRS are conceptually conservative but that inappropriate application of the conservatism principles is likely to prevent financial reporting from reaching the level of conservatism targeted by the IASB. Overall, this paper contributes to the literature on IFRS and can be useful to capital market supervisors who are monitoring the trends of the firms implementing K-IFRS. Additionally, our results inform stakeholders of the potentially negative effect of the greater flexibility permitted by IFRS and/or lack of appropriate enforcement on key dimensions of accounting quality. This has important implications for Korean regulators and standard setters as they review the cost and benefits of IFRS. Our study also sheds light on the importance of the institutional environment in achieving the targeted objectives for improving financial reporting quality.
This study is for the effective pretreatment and saccharification of lignocellulosic biomass for a transport fuel receiving attention. The waste water during the pretreatment of biomass is major factor for determining the price of biofuel. Therefore, we conducted high concentration of organosolv pretreatment for decline waste water and reusing the solvent. We confirmed effect of organosolv pretreatment by components analysis and enzymatic hydrolysis of pretreated biomass. The corn stover was used for and 99.5 wt% of ethanol as a organosolv pretreatment. The pretreatment condition was varied 130 to $190^{\circ}C$ during the designated reaction times and the effect of pretreatment was investigated by enzymatic hydrolysis. The highest glucose conversion was more than 68% the pretreatment condition of $190^{\circ}C$ for 70 min or more. The solid remaining was more than 70% and almost of cellulose and hemicellulose were survived.
Hydrogen energy is emphasized as a substitutable energy of carbon-based energy system in the future, since it is non-depletable and clean energy. Long term vision of Korean government on the national energy system is to promote hydrogen energy by 15% of final energy demand until 2040. This study analyzes economic impacts of hydrogen energy development employing a dynamic CGE model for Korea. Frontier technology such as hydrogen energy is featured as slow diffusion at the initial stage due to the learning effect and energy complementarity. Without government intervention, hydrogen energy would be produced upto 6.5% of final energy demand until 2040. However, if government subsidizes sales price of hydrogen energy by 10%, 20%, and 30%, share of hydrogen energy would increase 9.2%, 15.2%, and 37.7% of final energy demand. This result shows that the slow diffusion problem of hydrogen energy as frontier technology could be figured out by market incentive policy. On the other hand, production levels of transportation sector would increase while growth rate of oil and electricity sectors would decline. Household consumption would be affected negatively since increase of consumption due to the price decrease would be overwhelmed by income reduction owing to the increase of tax. Overall, GDP would not decrease or increase significantly since total production, investment, and export would increase even if household consumption declines.
In this study, we examine how land use zoning affects the land price controlling other variables such as road-facing condition of the land, land form, land age after its development and land size. We employ geographically weighted regression analysis which reflects spatial dependency as methodology with a data sample of land transaction price data of Jangyu, a new town, in Korea. The results of our empirical analysis show that the respective coefficients of traditional regression and geographically weighted regression are not significantly different. However, after calculating Moran's Index with residuals of both OLS and GWR models, we find that Moran's Index of GWR decreases around 26% compared to that of OLS model, thus improving the problem of spatial autoregression of residuals considerably. Unlike our expectation, though, in both traditional regression and geographically weighted regression where residential exclusive area is used as a reference variable, the dummy variable of the residential land for both housing and shops shows a negative sign. This may be because the residential land for both housing and shops is usually located in the level area while the residential exclusive area is located at the foot of a mountain or on a gentle hill where the residents can have good quality air and scenery. Although the utility of the residential land for both housing and shops is higher than its counterpart's since it has higher floor area ratio, amenity which can be explained as high quality of air and scenery in this study seems to have higher impact in purchase of land for housing. On the other hand, land for neighbourhood living facility seems to be valued higher than any other land zonings used in this research since it has much higher floor area ratio than the two land zonings above and can have a building with up to 5 stories constructed on it. With regard to road-facing condition, land buyers seem to prefer land which faces a medium-width road as expected. Land facing a wide-width road may have some disadvantage in that it can be exposed to noise and exhaust gas from cars and that entrance may not be easy due to the high speed traffic of the road. In contrast, land facing a narrow road can be free of noise or fume from cars and have privacy protected while it has some inconvenience in that entrance may be blocked by cars parked in both sides of the narrow road. Finally, land age variable shows a negative sign, which means that the price of land declines over time. This may be because decline of the land price of Jangyu was bigger than that of other regions in Gimhae where Jangyu, a new town, also belong, during the global financial crisis of 2008.
This study investigates the determinants of municipal water prices and costs in Korea. A panel data set of 164 municipalities for the period 2000~2007 is used for the study. Both random and fixed effect models with an appropriate set of instruments are applied to the data. Substantial differences in prices and costs among municipalities are observed. The study finds that prices and costs increase if the leakage rate is high, the quality of primary water is bad, and the municipality has to purchase primary water from K-water which is the single creation and management corporation of water resources facilities in Korea. Prices and costs decline if the size of consumer is large, the proportion of paying consumer is high, and the amount of subsidy from the central government is large.
Lim, Gyoo Gun;Noh, Jong Hwa;Lee, Hyun Tae;Ahn, Jae Ik
Journal of Information Technology Services
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v.21
no.3
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pp.63-72
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2022
The extinction crisis of local cities, caused by a population density increase phenomenon in capital regions, directly causes the increase of vacant houses in local cities. According to population and housing census, Gunsan-si has continuously shown increasing trend of vacant houses during 2015 to 2019. In particular, since Gunsan-si is the city which suffers from doughnut effect and industrial decline, problems regrading to vacant house seems to exacerbate. This study aims to provide a foundation of a system which can predict and deal with the building that has high risk of becoming vacant house through implementing a data driven vacant house prediction machine learning model. Methodologically, this study analyzes three types of machine learning model by differing the data components. First model is trained based on building register, individual declared land value, house price and socioeconomic data and second model is trained with the same data as first model but with additional POI(Point of Interest) data. Finally, third model is trained with same data as the second model but with excluding water usage and electricity usage data. As a result, second model shows the best performance based on F1-score. Random Forest, Gradient Boosting Machine, XGBoost and LightGBM which are tree ensemble series, show the best performance as a whole. Additionally, the complexity of the model can be reduced through eliminating independent variables that have correlation coefficient between the variables and vacant house status lower than the 0.1 based on absolute value. Finally, this study suggests XGBoost and LightGBM based machine learning model, which can handle missing values, as final vacant house prediction model.
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