• Title/Summary/Keyword: Panel data regression model

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Impacts of Financial Constraints on Firm Value for KONEX Listed Firms

  • Zhang, Xue Dong;Kang, Shinae
    • The Journal of Economics, Marketing and Management
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    • v.9 no.4
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    • pp.1-8
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    • 2021
  • Purpose: This study empirically investigates what factors contribute to corporate value in the Korea New Exchange (KONEX) market and determines whether financial constraints contribute any effect on it. Research design, data and methodology: A fixed-effect panel regression model was utilized to analyze financial constraints on firm value for KONEX listed firms through the fiscal period from 2013 to 2020. Results: we find that firms' research and development, volatility, size, and sales growth give significant impacts to firm value, but the significance and direction are different. In addition, no significant relationship exists between the largest shareholder's equity ratio and firm value in all models. The debt-to-equity ratio did not show a significant relationship with corporate value. A significant negative relationship was found between R&D and corporate value in the entire sample. Volitility exhibited a positive relationship with corporate value in the entire sample and financially unconstrained companies. Firm size presented a significant negative relationship with company value in all models. Sales growth showed a significant negative relationship with corporate value in financially constrained companies. Conclusions: No difference is found between financially constrained and unconstrained companies in the KONEX market. We can infer that KONEX companies have a large difference with KOSPI or KOSDAQ. Further analysis is needed on the differences among these markets.

Nuclear energy consumption, nuclear fusion reactors and environmental quality: The case of G7 countries

  • Cakar, Nigar Demircan;Erdogan, Seyfettin;Gedikli, Ayfer;Oncu, Mehmet Akif
    • Nuclear Engineering and Technology
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    • v.54 no.4
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    • pp.1301-1311
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    • 2022
  • Global climate change brings environmental quality sensitivity, especially in developed countries. Developed countries use non-renewable energy sources intensively both in their own countries and in other countries, they make productions that cause an enormous rate of increase in CO2 emissions and unsustainable environmental costs. This has increased the interest in environmentally friendly alternative energy sources. The aim of this study is to investigate the impact of nuclear energy consumption and technological innovation on environmental quality in G7 countries using annual data over the period 1970-2015. The Panel Threshold Regression Model was used for the analysis. Empirical findings have indicated that the relationship between nuclear energy consumption and carbon emissions differs according to innovation for nuclear power plants. It was also concluded that nuclear energy consumption reduces carbon emissions more after a certain level of innovation. This result shows that the increase in innovative technologies for nuclear power plants not only increases energy efficiency but also contributes positively to environmental quality.

Application of Generalized Maximum Entropy Estimator to the Two-way Nested Error Component Model with III-Posed Data

  • Cheon, Soo-Young
    • Communications for Statistical Applications and Methods
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    • v.16 no.4
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    • pp.659-667
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    • 2009
  • Recently Song and Cheon (2006) and Cheon and Lim (2009) developed the generalized maximum entropy(GME) estimator to solve ill-posed problems for the regression coefficients in the simple panel model. The models discussed consider the individual and a spatial autoregressive disturbance effects. However, in many application in economics the data may contain nested groupings. This paper considers a two-way error component model with nested groupings for the ill-posed data and proposes the GME estimator of the unknown parameters. The performance of this estimator is compared with the existing methods on the simulated dataset. The results indicate that the GME method performs the best in estimating the unknown parameters in terms of its quality when the data are ill-posed.

The Determinants of Foreign Investments in Korean Stock Market

  • KANG, Shinae
    • The Journal of Economics, Marketing and Management
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    • v.7 no.2
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    • pp.1-5
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    • 2019
  • Purpose - Along with the rise of foreign investments in the Korean stock market, there has been a variety of studies on their influence. The conflicting findings on the question of information asymmetry of foreign investors among existing literatures appear to be a result of mixture of research method problems, what information is defined as being comparable, individual business levels, or the entire stock market. This paper empirically investigates what factors contribute to foreign investments in firms in the Korean stock market. Research design, data, and Methodology - Samples are constructed by manufacturing firms listed on the stock market of Korea as well as those who settle accounts in December from 2001 to 2018. Financial institutions are excluded from the sample as their accounting procedures, governance and regulations differ. This study adopted the panel regression model to assess the sample construction including yearly and cross-sectional data. Result - This paper find that firms' R&D, dividends, size give significant positive impact to foreign investment, whereas debt gives significant negative impact to foreign investment. This relationship does not change when the samples are divided before and after the 2008 global financial crisis. Conclusion - This results support the literatures that foreign investors favor firms lowering their information asymmetry.

A Study on Spillover of Technology Trade against Post- BRICs (BRICs 이후 신흥국과의 기술무역 확산방안 연구)

  • Baek, Eun-Young
    • International Commerce and Information Review
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    • v.16 no.5
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    • pp.361-385
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    • 2014
  • This study focused on Spillover of Technology Trade against Post- BRICs of the Technology export of Korea. Therefore this study made an empirical analysis for investigating the competitiveness of technology export in Korea and using panel data 2003-2012 of technology trade data between 6 Countries(Indonesia, Mexico, Nigeria, South Africa, Turkey, Vietnam). In particular, the study deduced the correlation between technology export in Korea using the variables of Gross Domestic Expenditure on R&D and Per capita GDP, distance, population, free-trade index, FDI, Technology-Intensive Manufactures, Pattern Investment fixed effect model in panel linear regression model. It is found that the Technology export of Korea SMEs made a significant effect on the pop, free_trade, and distance. and also it is found that the Technology export of Korea Big Business made a significant effect on the per-GDP, Fdi from Korea, free_trade, and distance. The results suggest that the study should use technology gap variables and the strategy for activating the Technology export of Korea should be made for future works.

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An Empirical Test on Technology Export of Korea SMEs (우리나라 중소기업의 기술수출에 관한 실증연구)

  • Baek, Eun-Young
    • International Commerce and Information Review
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    • v.16 no.2
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    • pp.279-296
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    • 2014
  • This study focused on the Technology export of Korea SMEs. Therefore this study made an empirical analysis for investigating the competitiveness of technology export in Korea SMEs and using panel data 2003-2011 of technology trade data between 72 Countries. In particular, the study deduced the correlation between technology export in Korea SMEs using the variables of Gross Domestic Expenditure on R&D and Per capita GDP, distance, population, free-trade index, firm R&D against industry value added of country, Patent grants by country to USA fixed effect model in panel linear regression model. It is found that the Technology export of Korea SMEs made a significant effect on the per-GDP, Gross Domestic Expenditure on R&D. The results suggest that the study should use technology gap variables and the strategy for activating the Technology export of Korea SMEs should be made for future works.

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The Impact of Industrial Diversity to Unemployment and Employment Instability: An Analysis of Regional Economy Using Panel Regression Model (산업구조의 다양성이 실업과 고용불안정에 미치는 영향: 패널회귀모형을 이용한 지역경제 분석)

  • Ryu, Suyeol;Choi, Ki-Hong;Ko, Seung-Hwan;Yoon, Seong-Min
    • Journal of the Economic Geographical Society of Korea
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    • v.17 no.1
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    • pp.129-146
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    • 2014
  • This paper investigates how industrial diversity affects unemployment and employment instability from the perspective of the regional economy. Through this analysis, we examine how the industry-specific policy to promote some industry strategically in most of areas affects the stability of the regional economy. We measure Herfindahl indexes using the 1993-2010 data of 16 regions in Korea, and use panel regression model for empirical analysis. The main results from this empirical analysis are summarized as follows. First, we confirm that the industrial structure of most regions has been changed to the direction of specialization in 1990s and to the direction of diversification in 2000s through analyzing the changes in the values of Herfindahl indexes during the given period. Second, we find from the estimation results of panel regression model that the higher industrial diversity in most of regions is, the lower the unemployment rate is. However, a statistically significant relationship between industrial diversity and employment instability only partially confirmed. Third, there exist high unemployment rate and employment instability in most metropolitan areas, but it is hard to say that this relationship is highly statistically significant. From the results of the empirical analysis, it is likely that the industry-specific policies such as the regional strategic industry development policies unlike policy goals make the unemployment rate to rise and economic instability to increase. From the viewpoint of employment aspects, the strategies to increase industrial diversity would be desirable rather than those to specialize in the industrial structure.

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Gender Differences in Factors Affecting Purchase of Indemnity Private Health Insurance and Impact of Indemnity Private Health Insurance on Healthcare Use: Korea Health Panel Survey Data from 2010 to 2016 (실손형 민간의료보험 가입의 영향요인과 실손형 민간의료보험이 의료이용에 미치는 영향에서 성별 차이: 한국의료패널(2010-2016))

  • You, Chang Hoon;Kwon, Young Dae
    • The Journal of the Korea Contents Association
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    • v.20 no.3
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    • pp.92-105
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    • 2020
  • This study was aimed to identify factors affecting the purchase of indemnity private health insurance and analyze its effect on healthcare utilization by gender. This study analyzed data of the 2010-2016 Korea Health Panel Survey using panel logit model and panel regression model. Men were less likely to purchase indemnity private health insurance than women. Self-rated health and unmet need for healthcare in women were related to insurance purchases. In men, married people and residents of the metropolitan area were more likely to purchase. The indemnity private health insurance did not affect the women's outpatient expenses per visit, but for men it increased. The indemnity private health insurance significantly increased women's inpatient expenses per admission, but it did not affect men's inpatient expenses. This study confirmed gender differences in the factors affecting the purchase of indemnity health insurance and the impact of indemnity health insurance on healthcare utilization. This suggests that gender differences should be taken into account in private health insurance research and institutional operation.

The EU-South Korea FTA: Which Sector Benefits the Most?

  • Evert, Janik;Oh, Jinhwan
    • Journal of Korea Trade
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    • v.23 no.2
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    • pp.76-87
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    • 2019
  • Purpose - This study empirically analyzes the effects of the European Union-South Korea Free Trade Agreement on Korean exports in major sectors. Design/Methodology - This study is based on the augmented gravity model with a panel data set covering 51 countries between the years 2000 and 2015. Findings - Main findings of the present study is that the agreement has affected the chemical sector the most. Fixed effects estimation predicted a positive trade effect of 38.3%, while Poisson maximum likelihood estimation predicted an impact of 4.75% in the chemical export sector. Regression results for the other sectors only show insignificant effects. Originality/value - The findings imply that the effects of the EU-South Korea free trade agreement on the Korean exports are quite specific compared to the European ones, meaning that the Korean government should focus on sector-specific programs to maximize the welfare benefits of the free trade agreement.

FACTORS AFFECTING PRODUCTIVITY ON DAIRY FARMS IN TROPICAL AND SUB-TROPICAL ENVIRONMENTS

  • Kerr, D.V.;Davison, T.M.;Cowan, R.T.;Chaseling, J.
    • Asian-Australasian Journal of Animal Sciences
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    • v.8 no.5
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    • pp.505-513
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    • 1995
  • The major factors affecting productivity on daily farms in Queensland, Australia, were determined using the stepwise linear regression approach. The data were obtained from a survey conducted on the total population of daily farms in Queensland in 1987. These data were divided into six major dailying regions. The technique was applied using 12 independent variables believed by a panel of experienced research and extension personnel to exert the most influence on milk production. The regression equations were all significant (p < 0.001) with the percentage coefficients of determination ranging from 62 to 76% for equations developed using' total farm milk: production as the dependent variable. Three of the variables affecting total farm milk: production were found to be common to all six regions. These were; the amount of supplementary energy fed, the area set aside to irrigate winter feed and the size of the area used for dailying. Higher production farms appeared to be more efficient in that they consistently produced milk production levels higher than those estimated from the regression equation for their region. Other methods of analysis including robust regression and non linear regression techniques were unsuccessful in overcoming this problem and allowing development of a model appropriate for farms at all levels of production.