• Title/Summary/Keyword: Panel Data Regression

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Analysis on the Relationship between R&D Inputs and Performance by using Panel Data : Focus on Defense Industry (패널 데이터를 이용한 방위산업의 R&D 투입과 성과 관계 분석)

  • Lee, Kang-Taek;Kim, Geun-Hyung;Lee, Seung-Hyun;Lee, Ik-Do
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.12
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    • pp.491-497
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    • 2018
  • This study analyzes the relationship between R&D input and performance using panel data from the defense industry. A research model is established based on the R&D logic model, and the study sample consists of a strongly balanced panel data (n=351) empirically analyzed using panel linear regression. Results identified that defense improvement expenditure has a positive influence on the R&D input, and R&D input positively affected patents using a 5-year time lag. In addition, R&D input positively impacts economic performance, including sales and profit. Hence, the major finding includes R&D inputs have statistically significant effects on economic outcome and the R&D logic model featuring a time-lag.

A Study on the Determinants of Convalescent Rehabilitation Medical Service Needs at Regional Level (지역별 회복기 재활 의료서비스 필요도 결정요인 분석 연구)

  • Jung Hoon Kim;Heenyun Kim;Yongseok Choi;Hyoung Sun Jeong
    • Health Policy and Management
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    • v.33 no.1
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    • pp.40-54
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    • 2023
  • Background: Based on the increase in the needs for convalescent rehabilitation medical services in Korea, this study aims to calculate the needs for rehabilitation services and examine its determinants for 229 regions. Methods: Claim data from the Health Insurance Review and Assessment Service were used to estimate patients who need to receive rehabilitation services, and data from various sources were also used for analysis. The number of cases and incidence rates of hospitalization related to convalescent rehabilitation were calculated to estimate the needs for services by region, and the results were visualized via a map. Multivariate regression and fixed effects regression using panel data were performed to identify the determinants of regional variation of the incidence rate. Results: First, the incidence rate of rural areas such as Jeolla-do, Gyeongsang-do, and Chungcheong-do was higher than urban areas (metropolitan cities). Second, the population, proportion of the elder, medical aid recipients, financial independence, traffic deaths, smoking, diabetes rate, and medical infrastructure correlated significantly with the incidence rate. Third, 'rho' values which mean the fraction of variance due to individual terms in panel data regression models were 0.965 and 0.976, respectively. Conclusion: The incidence rate of hospitalizations was correlated with most independent variables in this study and there is a gap between urban and rural areas. These regional disparities are fixed in our society. An improved regional convalescent rehabilitation system is suggested to cover the entire area including rural areas with a high rate of aging.

Revisiting a Gravity Model of Immigration: A Panel Data Analysis of Economic Determinants

  • Kim, Kyunghun
    • East Asian Economic Review
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    • v.26 no.2
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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.

R&D and Environmental Kuznets Curve Hypothesis: CO2 Case (R&D 투자와 환경쿠즈네츠 곡선 가설: CO2 사례 분석)

  • Kang, Heechan;Hwang, Sangyeon
    • Environmental and Resource Economics Review
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    • v.25 no.1
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    • pp.89-112
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    • 2016
  • In this paper, as a determining factor of the Environment Kuznets Curve hypothesis, we analyzed the impact of technological innovation. In this paper, in order to empirically validate the role of technological innovation to an inverted U-shaped Environments Kuznets Curve hypothesis, we utilize the 2SLS considering relationship between R&D and the GDP per capita. Also, using the Panel VAR (Panel Vector Auto Regression) model to analyze with what time lag R&D per capita has impact on the emissions of greenhouse gases per capita. Empirical results show that R&D per capita(proxy of innovation) is a important factor to explain Environmental Kuznets Curve hypothesis, and that the external shock such as R&D per capita reduces greenhouse gas emissions per capita with about 3 time lag.

Wage Determinants Analysis by Quantile Regression Tree

  • Chang, Young-Jae
    • Communications for Statistical Applications and Methods
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    • v.19 no.2
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    • pp.293-301
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    • 2012
  • Quantile regression proposed by Koenker and Bassett (1978) is a statistical technique that estimates conditional quantiles. The advantage of using quantile regression is the robustness in response to large outliers compared to ordinary least squares(OLS) regression. A regression tree approach has been applied to OLS problems to fit flexible models. Loh (2002) proposed the GUIDE algorithm that has a negligible selection bias and relatively low computational cost. Quantile regression can be regarded as an analogue of OLS, therefore it can also be applied to GUIDE regression tree method. Chaudhuri and Loh (2002) proposed a nonparametric quantile regression method that blends key features of piecewise polynomial quantile regression and tree-structured regression based on adaptive recursive partitioning. Lee and Lee (2006) investigated wage determinants in the Korean labor market using the Korean Labor and Income Panel Study(KLIPS). Following Lee and Lee, we fit three kinds of quantile regression tree models to KLIPS data with respect to the quantiles, 0.05, 0.2, 0.5, 0.8, and 0.95. Among the three models, multiple linear piecewise quantile regression model forms the shortest tree structure, while the piecewise constant quantile regression model has a deeper tree structure with more terminal nodes in general. Age, gender, marriage status, and education seem to be the determinants of the wage level throughout the quantiles; in addition, education experience appears as the important determinant of the wage level in the highly paid group.

Study on Effects of Meteorological Elements in the Grain Production of Korea (우리나라 곡물류 생산량에 기상요소의 영향에 관한 연구)

  • Chang, Young-Jae;Lee, Joong-Woo;Park, Jong-Kil;Park, Heung Jai
    • Journal of Environmental Science International
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    • v.24 no.3
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    • pp.281-290
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    • 2015
  • 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 on the production of five types of grain with error component panel data regression method following the test results of LM tests, Hausman test. The key factors affecting the production of rice were average temperature, average relative humidity and average ground surface temperature. The fluctuations in the other four grains types are not well explained by meterological elements. For other grains and beans, only average temperature and time (year) affect the production of other grains while average temperature, ground surface temperature, and time (year) influence the production of beans. For barley and millet, only average temperature positively affects the production of barley while ground surface temperature and time (year) negatively influence the production of millet. The implications of this study are as follow. First, it was confirmed that the meteorological elements have profound effects on the rice production. Second, when compared to existing studies, this study was not limited to rice but encompassed all five types of grains and went beyond other studies that were limited to temperature and rainfall to include various meteorological elements.

Analysis of Unmet Healthcare Needs and Risk Factors to Improve the Life Care of Osteoporosis Patients (골다공증 환자의 라이프 케어 증진을 위한 미충족 의료실태와 위험요인 분석)

  • Park, Hyeon-Hee
    • Journal of Korea Entertainment Industry Association
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    • v.14 no.2
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    • pp.225-235
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    • 2020
  • Purpose: This study is a descriptive and secondary analytical study that uses panel data to analysis of unmet healthcare needs and risk factors for improving life care of osteoporosis patients. Methods: The subjects of this study were 941 patients who were diagnosed with osteoporosis using Korea Medical Panel 2015 data(β-version 1.0). Data analysis was performed using Chi-Square and logistic regression using SPSS/win 22.0. Results: The unmet healthcare needs of osteoporosis patients were 22.6%. The factors of unmet healthcare needs were education level and age in Model I of demographic factors, and eating problems, memory problems, activity limitation, and disability in Model II. In Model III, which added socio-psychological factors, eating problems, memory problems, Total family income, and pain/Discomfort were identified. Conclusion: Based on the results of this study, it should be considered in the planning of medical policies to improve the life care of osteoporosis patients, and it is necessary to improve access to medical services and to prevent and mediate realistically to reduce unmet healthcare needs.

Analysis of Factors Related to the Use of Korean Medicine Treatment in Patients with Mood Disorders: Based on 2019 Korea Health Panel Annual Data (기분장애 환자에서 한의치료 이용과 관련된 요인분석: 제2기 한국의료패널 자료를 중심으로)

  • Kyoungeun Lee;Chan-Young Kwon
    • Journal of Oriental Neuropsychiatry
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    • v.34 no.4
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    • pp.349-358
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    • 2023
  • Objectives: We used the 2019 Korea Health Panel Annual Data to analyze factors related to visits to Korean medicine (KM) outpatient clinics among patients with mood disorders in Korea. Methods: Individuals aged 19 years or older, with depressive or bipolar disorders, and with a record of using Western medicine (WM) and/or the KM medical service were included. The 266 subjects were classified into the WM group or the integrative medicine (IM) group. The Andersen healthcare utilization model was used to analyze factors that potentially influenced the subjects' healthcare utilization. Binomial logistic regression analysis was used to analyze factors influencing the use of IM medical services. Results: Among the subjects, 75.56% (n=201) were in the WM group, and 24.44% (n=65) were in the IM group. Statistically significant differences were observed in residential areas, total annual income, the presence of disability, and the level of pain/discomfort between the two groups. Regression analysis found that residential areas and pain/discomfort were factors related to the use of IM services. Specifically, reporting "a lot" of pain/discomfort compared to "no" pain/discomfort showed a significant positive relationship with the use of IM (odds ratio=4.57, 95% confidence interval=1.79 to 11.70). Conclusions: This study was the first to analyze the status of KM medical service use and related factors among patients with mood disorders in Korea. The finding that the presence of pain/discomfort was positively correlated with the use of KM services is potentially related to medically unexplained physical symptoms or somatization phenomena.

Analysis of Factors Related to the Use of Both Korean and Western Medicine Treatment in Patients with Overweight and Obesity: Based on the Korea Health Panel Annual Data 2019 (과체중 및 비만 환자에서 한·양방 의료 이용과 관련된 요인분석: 제2기 한국의료패널 자료를 중심으로)

  • Chan-Young Kwon
    • Journal of Korean Medicine for Obesity Research
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    • v.24 no.1
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    • pp.41-53
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    • 2024
  • Objectives: We used the Korea Health Panel Annual Data 2019 to analyze factors related to visits to both Korean medicine and Western medicine (WM) outpatient clinics among patients with overweight and obesity. Methods: The inclusion criteria for this study are as follows: 1) adults over 18 years of age, 2) overweight or obese with a body mass index of 25.0 or more, 3) visited WM outpatient clinics at least once during 2019. Total 2,963 individuals were included in WM group or integrative medicine (IM) group. Using the Andersen healthcare utilization model, factors related to healthcare utilization of the participants were classified. Binomial logistic regression analysis was used to analyze factors associated with IM use. Results: Among the participants, 80.49% (n=2,385) were assigned to WM group and 19.51% (n=578) to IM group. As a result of the regression analysis, factors significantly related to the use of IM included the elderly over 65 years of age, sex (men), college or higher education level, residential area (Gwangju/Jeolla/Jeju), presence of cancer, and presence of musculoskeletal disease. The main diagnosis associated with both WM and IM use was most frequently musculoskeletal conditions. Also, IM group received WM treatment for musculoskeletal conditions more frequently compared to WM group. Conclusions: This study is the first to analyze healthcare utilization patterns among overweight or obese patients in Korea. The current findings suggest that the presence of musculoskeletal conditions, especially in this population, may be strongly associated with concurrent use of IM services.

Audit Quality and Stock Return Co-Movement: Evidence from Vietnam

  • PHAM, Chi Bich Thi;VU, Thu Minh Thi;NGUYEN, Linh Ha;NGUYEN, Dung Duc
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.7
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    • pp.139-147
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    • 2020
  • This paper aims to explore the relationship between the quality of the audit and the level of stock return co-movement in the context of the Vietnamese emerging market. The empirical study is designed based on the quatitative method and deductive approach. The panel dataset includes 256 listed firms from different industries,with 1115 firm-year observations on Ho Chi Minh City Stock Exchange for the period from 2014 to 2018. In the research, we built the econometric regression model, using stock return synchronicity and audit quality as the dependent and independent variable, respectively. Some control variables are also added to the econometric regression models as they are well-documented in prior research to have an effect on stock price synchronicity. To improve the accuracy of the regression coefficients, beside the Ordinary Least Squares, we employ the Random Effects Model and the Fixed Effects Model for better statistical analysis of panel data set. The results show that the quality of the audit is positively correlated to stock price synchronicity. This finding suggests that stock returns of companies with higher quality of the audit are more synchronous with the market. Results for other control variables also support our reasoning for the main findings.