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

• Review of Culture and Economy
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• v.21 no.3
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• pp.59-88
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• 2018

This study examines demand of the Korean TV VOD using monthly aggregate data and time series analysis models. In particular, the impact of box office attendance, number of IPTV subscribers, income and price of substitutes on TV VOD market is analyzed. Data on TV VOD download during the period 2013 January to 2018 June are used for the empirical analysis. TV VOD demand shows lower level of seasonality than box office attendance and the share of monthly top1 movie in TV VOD platform is also lower than that of box office attendance. The relationship between a movie's holdback and box office performance does not seem consistent. The empirical result of ARDL model reveals that in the short-run box office attendance, number of IPTV subscribers and price of substitutes have significant impact on TV VOD demand. The result on the long-term relation shows that income is the only determinant of TV VOD demand. The impact of box office attendance on TV VOD is not shown to be robust both for the short-term and long-term.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.9
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• pp.263-269
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• 2022

The global financial crisis of 2008-2009 and the COVID-19 pandemic that started in 2019 along with the slow and unstable recovery of the global economy have raised concerns about the impact of global uncertainty on the macroeconomics of the countries. The paper used the Structural Vector Autoregression (SVAR) model to examine the impact of global uncertainty shocks on Vietnam's economy from the period 2008-2022. We found that Vietnam's output dropped following the shock of global uncertainty, the peak was in the third month, and lasted for one year. Inflation in Vietnam had a rapid downturn in the first month, peaked in the seventh month, and took a long time to cease. When the economy experienced the shock of increased global uncertainty, Vietnam's policy interest rate was adjusted downward. Additionally, we included a long-term interest rate to consider the overall impact of monetary policy into account. A decreasing trend was also found with this rate. The global uncertainty shock effects acted as the aggregate demand shocks, reducing output and inflation as the uncertainty increases and vice versa, thus monetary policy can be used to regulate Vietnam's economy to deal with negative shocks without the trade-offs between output and inflation as aggregate supply shocks.

• KDI Journal of Economic Policy
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• v.12 no.4
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• pp.3-20
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• 1990

The multisector model is designed to analyze and forecast structural change in industrial output, employment, capital and relative price as well as macroeconomic change in aggregate income, interest rate, etc. This model has 25 industrial sectors, containing about 1,300 equations. Therefore, this model is characterized by detailed structural disaggregation at the sectoral level. Individual industries are based on many of the economic relationships in the model. This is what distinguishes a multisector model from a macroeconomic model. Each industry is a behavioral agent in the model for industrial investment, employment, prices, wages, and intermediate demand. The strength of the model lies in the simulating the interactions between different industries. The result of its simulation will be introduced in the next paper. In this paper, we only introduce the structure of the multisector model and the coefficients of the equations. The multisector model is a dynamic model-that is, it solves year by year into the future using its own solutions for earlier years. The development of a dynamic, year-by-year solution allows us to combine the change in structure with a consideration of the dynamic adjustment required. These dynamics have obvious advantages in the use of the multisector model for industrial planning. The multisector model is a medium-term and long-term model. Whereas a short-term model can taken the labor supply and capital stock as given, a long-term model must acknowledge that these are determined endogenously. Changes in the medium-term can be analyzed in the context of long-term structural changes. The structure of this model can be summarized as follow. The difference in domestic and world prices affects industrial structure and the pattern of international trade; domestic output and factor price affect factor demand; factor demand and factor price affect industrial income; industrial income and relative price affect industrial consumption. Technical progress, as measured in terms of total factor productivity and relative price affect input-output coefficients; input-output coefficients and relative price determine the industrial input cost; input cost and import price determine domestic price. The differences in productivity and wage growth among different industries affect the relative price.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.143-150
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• 2014

Cloud computing is fast becoming the wave of the future for both home and business computing. Because of this growing acceptance, we can expect an explosion of diverse cloud service providers in the coming years. However, the cloud is not a single entity, rather it is a set of many disconnected islands of application (SaaS), infrastructure (IaaS), and different platform (PaaS) services. Cloud brokering mechanisms are essential to transform the heterogeneous cloud market into a commodity-like service. Cloud service brokers (CSBs) are the new form of business entities to help to aggregate the scattered set of cloud services and make conveniently available to their diverse users. CSBs can reserve a certain percentage of their clients' (users') demand and satisfy the remaining portion in an on-demand basis. In doing so, they need to minimize cost of both reserved and on-demand instances as well as the distance of a link between the cloud service provider (CSP) and the user. The study proposes a reservation approach with a mixed integer model to optimizes the cloud service cost and quality.

• Journal of Navigation and Port Research
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• v.31 no.10
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• pp.885-890
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• 2007

The purpose of this study is for providing a strategic plan of waterfront belt development at the coastal area of Busan city that might enhance the possibility on healthy use of spare time of the residents and demand of tourism, together with raising the potential and the value added effect of coastal space. This study is one of a series of studies for developing waterfront belt at Busan coastal area. In this study we suggest the new concepts of waterfront belt, waterfront cluster and waterfront greenway. And then we present a model of making waterfront belt through waterfront cluster, which is an aggregate of individual waterfront spaces, using waterfront greenway. After that we apply this model to Haeundae coastal area and test the applicability of the model.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.229-256
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• 2023

The increase in telecommuting and household electricity demand due to the pandemic has led to significant changes in electricity demand patterns. This has led to difficulties in identifying KEPCO's PPA (power purchase agreements) and residential solar power generation and has added to the challenges of electricity demand forecasting and grid operation for power exchanges. Unlike other energy resources, electricity is difficult to store, so it is essential to maintain a balance between energy production and consumption. A shortage or overproduction of electricity can cause significant instability in the energy system, so it is necessary to manage the supply and demand of electricity effectively. Especially in the Fourth Industrial Revolution, the importance of data has increased, and problems such as large-scale fires and power outages can have a severe impact. Therefore, in the field of electricity, it is crucial to accurately predict the amount of power generation, such as renewable energy, along with the exact demand for electricity, for proper power generation management, which helps to reduce unnecessary power production and efficiently utilize energy resources. In this study, we reviewed the renewable energy generation forecasting system, its objectives, and practical applications to construct optimal aggregated power resources using data from 169 power plants provided by the Ministry of Trade, Industry, and Energy, developed an aggregation algorithm considering the settlement of the forecasting system, and applied it to the analytical logic to synthesize and interpret the results. This study developed an optimal aggregation algorithm and derived an aggregation configuration (Result_Number 546) that reached 80.66% of the maximum settlement amount and identified plants that increase the settlement amount (B1783, B1729, N6002, S5044, B1782, N6006) and plants that decrease the settlement amount (S5034, S5023, S5031) when aggregating plants. This study is significant as the first study to develop an optimal aggregation algorithm using aggregated power resources as a research unit, and we expect that the results of this study can be used to improve the stability of the power system and efficiently utilize energy resources.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.113-122
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• 2021

This study aims to investigate the effects of fiscal policy instruments on economic growth in Jordan using annual data from 1970 to 2019, by applying the VAR model (Vector Auto regression) and the Vector Error Correction Model (VECM). The study also examines the dynamic relationship among economic variables over time using the Granger casualty test, Impulse Response Function, and Variance Decomposition. The results show that not only the public expenditures have a positive effect on economic growth in Jordan, but also the tax revenues positively affect the economic growth in the short-run, and this is because of using the tax revenues to finance the government activities in Jordan. This effect becomes negative in the long run, and this is explained because the tax seems a source of distortions in the economy, The extreme taxes may cause huge distortions in the economy, and these distortions destroys the purchasing power, the aggregate demand, and supply. More governmental dependence on tax revenues is the main source of tax evasion and less efficiency. The effect of taxation will curb any prosperity in the economy. Therefore, the government should estimate the fair tax rates to generate sufficient revenues to finance the public expenditure required to enhance economic prosperity.

• Journal of Korea Water Resources Association
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• v.30 no.4
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• pp.367-377
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• 1997

In order to set public policy to overcome 'water crises' on both quantity and quality of water, we looked into the national-economic role of Korea water utility by two approaches. First, we examined the relationship between water consumption and economic growth during 1978-94, a period of rapid increase in water consumption caused by prompt industrialization and urbanization. The price and income elasticities of aggregate and sectoral demand for water were estimated. Second, we developed a static input-output(I-O) framework for analysing water issues in the short run. In addition, we discussed two topics in its application: i) sectoral failure(shortage) costs by supply-driven I-O model, ii) Leontief price model's sectoral pervasive effects of price due to rise in water rate. In conclusion, we found that investments to water sector and water shortage has a big influence on the standard of living and industrial production. Also we found that raising water rate to encourage conservation or to create investment funds decreases demand for water significantly but has a small influence on overall price levels.

• Journal of Korean Society of Transportation
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• v.29 no.6
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• pp.97-106
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• 2011

Mode choice model is an essential element for estimating- the demand of new means of transportation in the planning stage as well as in the establishment phase. In general, current demand analysis model developed for the mode choice analysis applies common parameters of utility function in each region which causes inaccuracy in forecasting mode choice behavior. Several critical problems from using common parameters are: a common parameter set can not reflect different distribution of coefficient for travel time and travel cost by different population. Consequently, the resulting model fails to accurately explain policy variables such as travel time and travel cost. In particular, the nonlinear logit model applied to aggregation data is vulnerable to the aggregation error. The purpose of this paper is to consider the regional characteristics by adopting the parameters fitted to each area, so as to reduce prediction errors and enhance accuracy of the resulting mode choice model. In order to estimate parameter of each area, this study used Household Travel Survey Data of Metropolitan Transportation Authority. For the verification of the model, the value of time by marginal rate of substitution is evaluated and statistical test for resulting coefficients is also carried out. In order to crosscheck the applicability and reliability of the model, changes in mode choice are analyzed when Seoul subway line 9 is newly opened and the results are compared with those from the existing model developed without considering the regional characteristics.