• 의정연구
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• 제23권2호
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• pp.147-177
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• 2017

한국 선거에서 정치 이념의 역할에 대해 그동안 수많은 연구가 이루어졌으나, 지금까지의 연구들은 예외 없이 횡단면 데이터(cross-sectional data) 분석에 전적으로 의존하였다. 기존의 연구들과 달리 이 연구는 지난 제18대 대통령 선거에서 나타난 이념 투표의 영향을 패널 데이터 분석(panel data analysis)을 통해 보다 엄밀하게 검증한다. 구체적으로, "EAI 총선대선패널조사, 2012"를 이용하여 지난 18대 대통령 선거 시기(2012년 4월 중순-12월 하순)에 정치적이념이 유권자들의 후보 호오도(candidate evaluation)와 후보 선택(vote choice)에 미친 영향을 고정 효과(fixed effects) 분석과 변동 효과(random effect) 분석 등 표준적인 패널 데이터 분석을 통해 살펴보았다. 또한 이념투표의 대표적 설명 모형인 근접성 모형(proximity model)과 방향성 모형(directional change model)을 적용한 결과를 비교 분석하였다. 분석 결과, 지난 18대 대통령 선거에서 진보와 보수의 정치적 이념은 박근혜와 문재인후보에 대한 호오도 및 이들에 대한 지지에 독립적이고 유의미한 영향을 미쳤다고 할 수 있다. 즉, 유권자들은 특정 후보와의 이념적 차이가 크다고 느낄수록 그후보에 대한 지지 확률 및 호오도가 상대적으로 낮아졌다. 그리고 이러한 이념투표의 영향은 근접성 모형보다 방향성 모형에서 상대적으로 뚜렷하게 나타났다.

• 응용통계연구
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• 제29권5호
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• pp.873-885
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• 2016

노지에서 재배되는 양파 생산량은 기후환경에 의하여 영향을 받으며, 특정 지역에서 많이 생산되는 지역적인 특성을 가지고 있다. 따라서 생산량 예측시 기상과 지역을 동시에 고려하는 접근이 필요하다. 본 논문에서는 공간 패널 회귀모형을 이용하여 기상변화에 따른 생산량을 추정하였다. 양파 주산지 13곳에 대한 2006년부터 2015년까지의 기상 패널자료를 사용하여, 공간시차를 반영한 공간자기회귀(spatial autoregressive)모형을 사용하였다. 공간가중치 행렬은 임계치 설정방법과 최근거리 설정방법으로 나누어 분석하여, 최근 3곳까지 거리 설정방법을 사용한 모형이 최종 모형으로 선택되었으며, 자기상관성이 유의함을 보였다. 하우스만 검정을 통해 채택된 확률효과모형으로 분석한 결과 누적일조시간(1월), 평균상대습도(4월), 평균최저기온(6월), 누적강수량(11월) 등이 양파 생산량 예측에 유의한 변수로 나타났다.

• 응용통계연구
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• 제19권3호
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• pp.521-534
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• 2006

횡단면 자료와 시계열 자료가 병합된 패널회귀모형을 다루는 대부분의 연구들에서 사용되고 있는 자료는 완전한 자료를 고려하고 있다. 그러나, 실제적으로 완전한 자료보다는 불완전한 자료가 많다. 이러한 상황을 고려하지 않고 통계적인 추론을 하게 되면 잘못된 결론이 도출될 수 있다. 따라서, 자료의 형태를 충분히 고려한 추정량을 바탕으로 자료를 분석해야 한다. 본 연구는 패널회귀모형에서 자료가 불완전 상태인 경우 최대 엔트로피 형식을 이용한 일반화최대엔트로피 추정량을 제안하고, 추정량들의 효율성을 모의실험을 통하여 비교하였다. 모의실험 결과, 일반화 최대엔트로피 추정량이 가장 안정적이고 효율적인 추정량임을 보여주었다.

• 한국환경과학회지
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• 제22권9호
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• pp.1171-1180
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• 2013

Recent climate change has led to fluctuations in agricultural production, and as a result national food supply has become an important strategic factor in economic policy. As such, in this study, panel data was collected to analyze the effects of seven meteorological elements and using the Lagrange multipliers method, the fixed-effects model for the production of five types of food crop and the seven meteorological elements were analyzed. Results showed that the key factors effecting increases in production of rice grains were average temperature, average relative humidity and average ground surface temperature, while wheat and barley were found to have positive correlations with average temperature and average humidity. The implications of this study are as follow. First, it was confirmed that the meteorological elements have profound effects on the production of food crops. Second, when compared to existing studies, the study was not limited to one food crop but encompassed all five types, and went beyond other studies that were limited to temperature and rainfall to include various meterological elements.

• 한국환경과학회지
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• 제27권3호
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• pp.147-154
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• 2018

The purpose of this article is analyzing the impacts of seawater surface temperature rise on sea mustard yields of Goheung and Wando coast in Korea, with employing a panel data regression model. Our results show that there has been a negative impacts on sea mustard yields as seawater surface temperature continuously has been rising. Especially if the upward trend in seawater surface temperature since 2005 will be maintained in future, sea mustard yield is expected to decrease by 2.6% per year.

• Journal of the Korean Statistical Society
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• 제29권1호
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• pp.63-80
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• 2000

We consider the panel data regression model with nested error componets. In this paper, the several Lagrange Multipler tests for the nested error component model are derived. These tests extend the earlier work of Honda(1985), Moulton and Randolph(1989), Baltagi, et al.(1992) and King and Wu(1997) to the nested error component case. Monte Carlo experiments are conducted to study the performance of these LM tests.

• 보건행정학회지
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• 제14권2호
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• pp.99-116
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• 2004

This study estimates the determinants of national health expenditures of OECD countries using panel regression method. The data used are OECD Health Data(2003) covering 33 countries and from 1970 to 2001. This study shows several important different results compared to the previous studies. Further this study estimates the determinants of Korean case using data from 1m to 2000, and compare with the results of OECD panel. The main findings are as follows. The income elasticity of health expenditures is estimated below 1.0, but is shown above 1.0 when the different health systems of each country are controlled. The women's labor participation influences strongly positive effect on the health expenditures. The diffusion of new technologies is positively related with the increasing expense. The increasing government expenditures have a tendency not to contain health expenses, but to increase expenses. The expansion of public health insurance holders is containing the expenses, and the increasing number of doctors is pushing expenditures. This implies the health expenditures are influenced more by the induced demand of providers rather than the moral hazard of patients. However, the above result is opposite in Korean case. The existence of primary care doctors affects slightly up warding rather than containing expenditures. Finally the determinants are seriously depending upon which factors are included in the model and which statistical model is chosen. Therefore it must be cautious to interpret the results of statistical model.

• East Asian Economic Review
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• 제26권2호
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• pp.143-169
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• 2022

This study investigates the effect of economic factors on immigration using the gravity model of immigration. Cross-sectional regression and panel data analyses are conducted from 2000 to 2019 using the OECD International Migration Database, which consists of 36 destination countries and 201 countries of origin. The Poisson pseudo-maximum-likelihood method, which can effectively correct potential biased estimates caused by zeros in the immigration data, is used for estimation. The results indicate that the economic factors strengthened after the global financial crisis. Additionally, this effect varies depending on the type of immigration (the income level of origin country). The gravity model applied to immigration performs reasonably well, but it is necessary to consider the country-specific and time-varying characteristics.

• Asian Journal of Business Environment
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• 제13권1호
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• pp.31-41
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• 2023

Purpose: This study purposes to analyze the determinants of the volume of Indonesian tuna exports. Research design, data and methodology: The framework was developed from the gravity model for trade, which was expanded with additional variables of competitiveness, exchange rate, and industrial share of the destination country. The data sources used in this study are UN Comtrade and the World Bank. The data used is yearly data from 12 countries in 2001-2019. The scope of the study is limited to exports to the twelve main export destinations. Panel data regression analysis is used to determine the factors that affect the volume of Indonesian tuna exports. Results: The results show that according to the theory, Indonesia's GDP has a positive effect and economic distance has a negative effect on the volume of the exports. Meanwhile, the GDPs of the destination countries are not proven to have a positive effect. However, the higher the industrial share in the country, the higher the export volume tends to be. Conclusions: The conclusion obtained from this study is that Indonesia's GDP, economic distance, real exchange rate, industrial GDP share of the destination country, and the RCA index affect the volume of Indonesian tuna exports.

• The Journal of Asian Finance, Economics and Business
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• 제8권7호
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• pp.43-54
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• 2021

Human capital and innovation capacities are essential elements and one of the sustainable approaches to driving economic growth. However, there is debate among scholars concerning these two factors in fostering economic growth. This study investigates the relationships between human capital and innovation capacity and economic growth in selected ASEAN countries, namely, Malaysia, Thailand, and Indonesia. Economists widely discussed the interrelation of human capital and innovation. A large body of literature stated that human capital is an essential factor and engine of economic growth. Innovation has become key in transforming the economic development of developing countries. We analyze human capital (HC) and innovation capacity (INC) using static panel data analysis. The data analysis shows that the fixed-effect model is the best model in this study. Further, human capital (HC) has a significant positive relationship with economic growth. Meanwhile, innovation capacity has no significant relationship with economic growth. We also found that Malaysia's coefficient of human capital and innovation capacity is higher and more efficient than in Thailand and Indonesia. In conclusion, human capital and innovation capacity are crucial elements for measuring economic growth. Skilled human capital contributes significantly to the economic growth and economic development of a nation.