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김성찬(Sungchan Kim),박소영(Soyoung Park) 한국비교정부학회 2022 한국비교정부학보 Vol.26 No.1
(Purpose) The amount of the general shared tax can be determined primarily through standard financial demand, and a formula exists to calculate the amount. The majority of these factors are strongly related to population size, either directly or indirectly. Therefore, standard financial demand is likely affected by population size as well. However, large cities as subnational governments are also facing balanced regional development issues. Thus, this study explores how the population factor affects the amount of the general shared tax, as well as how large cities benefit from their population size. (Design/methodology/approach) For the analysis, we employ a panel data set comprised of 83 cities in South Korea from 2010 to 2018. (Findings) The results show that population size is negatively related to the amount of the general shared tax due to the economies of scale. However, large cities are free from the economies of scale while population can reduce the volatility of the tax amount in large cities. In addition, large cities are motivated if their population is increased. (Research implications or Originality) We conclude that large cities in South Korea do not benefit from their size. In order to increase population, additional supports and incentives are necessary, especially in large cities even though they have gotten more incentives since 2022, because they have greater economies of scale than other cities, while a balanced development policy must offer more help to small and isolated cities.
Cutback Management, Fiscal Stability, and Fiscal Outcome
김성찬(Sungchan Kim) 한국비교정부학회 2021 한국비교정부학보 Vol.25 No.2
(Purpose) Decision makers attempt to adopt strategies in order to treat the sensitivity of state budgets and stabilize the budgets throughout changes in the business cycle. Particularly, during times of fiscal stress or scarcity, public organizations have faced the necessity of cutbacks and implemented cutback management. However, there is little research about the effectiveness of cutback management. Thus, this study examines the impact of cutback strategies on spending stability and budgetary prerformance by using the data set of U.S. state governments from 2001 to 2013. (Design/methodology/approach) In my analysis, the ordinary least squares (OLS) model with random effect are used to see how cutback management affects total expenditure volatility and fiscal outcomes. Further, interaction terms between cutback management and state government savings as well as between cutback management and fiscal severity are also included in the analysis. (Findings) I find that cutback management strategies result in negative budgetary performance, which indicates that they are not generally effective. However, targeted cuts play a role in stabilizing expenditures in the short-term. Interestingly, this study finds that cutback management shows different outcomes when the cutback strategies are implemented in different contexts in terms of reousrce levels and fiscal severity of state governments. (Research implication or originality) This study shows that implementation of cutback management needs to consider other conditions of the government such as resources (savings) when the cutback is employed. State with higher levels of savings should accompany either the across-the-board or the targeted cuts with spending stability. Moreover, this study suggests that governments need to consider fiscal severity when cutback management is employed. In addition, in terms of short-term fiscal outcomes, states with a high level of fiscal severity need to employ targeted cuts for improving fiscal outcomes, but states with a higher level of fiscal severity are encouraged to implement the across-the-board cuts for fiscal outcomes in the longer term.
멀티 프로세서 시스템-온-칩(MPSoC)을 위한 버스 매트릭스 구조의 빠르고 정확한 성능 예측 기법 (pp.527-539)
김성찬(Sungchan Kim),하순희(Soonhoi Ha) 한국정보과학회 2008 정보과학회논문지 : 시스템 및 이론 Vol.35 No.11·12
본 논문은 큐잉 이론을 이용한 멀티 프로세서 시스템-온-칩(MPSoC)의 버스 매트릭스 기반 통신 구조에 대한 성능 예측 기법을 제안한다. 버스 매트릭스 기반 통신 구조는 다양한 설계 인자를 가지고 있어 이에 대한 성능 최적화는 방대한 설계 공간의 탐색을 필요로 하지만, 현재 널리 사용되고 있는 시뮬레이션에 기반한 방법은 많은 시간을 요구하기 때문에 점점 짧아지고 있는 시장 적기 출하(time-to-market) 제약 조건을 만족하기 어렵다. 이러한 문제를 해결하기 위하여 본 논문에서는 시뮬레이션보다 훨씬 빠르면서 정확하게 성능을 예측할 수 있는 기법을 개발하였다. 제안한 성능 분석 기법은 고성능의 버스 매트릭스를 위해 사용되는 버스 프로토콜인 multiple-outstanding transaction을 고려한다. 또한 지수 분포(exponential distribution)를 이용하여 비현실적으로 메모리 시스템을 모델하였던 기존의 연구들과 달리 실제적인 메모리 시스템 모델을 위하여 일반 분포(general distribution)를 이용하였다. 제안한 성능 예측 기법의 정확도 및 효율성을 검증하기 위하여 무작위로 생성된 버스 트랜잭션들과 4-채널 DVR 예제에 적용하였을 때, 사이클 단위의 정확도를 갖는 시뮬레이션과 비교하여 105배 이상 빠르면서 평균 94% 이상의 정확도를 갖는 것으로 분석되었다. This paper presents a performance estimation technique based on queuing analysis for on-chip bus matrix architectures of Multi-Processor System-on-Chips(MPSoCs). Previous works relying on time-consuming simulation are not able to explore the vast design space to cope with increasing time-to-market pressure. The proposed technique gives accurate estimation results while achieving faster estimation time than cycle-accurate simulation by order of magnitude. We consider the followings for the modeling of practical memory subsystem: (1) the service time with the general distribution instead of the exponential distribution and (2) multiple-outstanding transactions to achieve high performance. The experimental results show that the proposed analysis technique has the accuracy of 94% on average and much shorter runtime (105 times faster at least) compared to simulation for the various examples: the synthetic traces and real-time application, 4-channel DVR.