• Title/Summary/Keyword: lagged dependent variable

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An Empirical Analysis on the Determinants for Industrial Markup in the Korean Service Industries Using the ADL Scheme (자기회귀모형을 이용한 서비스산업의 마크업 결정요인에 관한 실증분석)

  • Hua, Zhu Yan;Park, Sehoon;Jung, Yong Sik
    • Journal of Korea Society of Industrial Information Systems
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    • v.19 no.6
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    • pp.87-96
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    • 2014
  • Since markup is defined as price over marginal cost by Hall(1988), the New Keynesians have intensively applied its definition in elucidating the relationship between market structure and business cycle. In lots of literatures markups proved to be counter cyclical empirically and theoretically. At the same time many studies analysed the determinants for markup in relation with business cycles. This paper establishes the markup equation based on the constant returns to scale production function including intermediate goods with technology being assumed to be AR(1) process and estimates the industrial markups in the Korean 5 service industries over the period 1975:1-2010:4. The paper also analyzed the markup determinants using the autoregressive distributed lag scheme ADL(1,1) in which the dependent variable and the single explanatory variable are each lagged once.

The Effect of R&D Investment on Local Economies Using Dynamic Panel Estimator in Korea (동태적 Panel 분석을 통한 R&D투자의 지역효과 분석)

  • Yang, Ji-Chung
    • International Area Studies Review
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    • v.18 no.3
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    • pp.175-201
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    • 2014
  • This paper analyses the effect of R&D investment on local economies. R&D investment contributes to the regional local economy by increasing employment and production activity of the investees. The investees may end up with increased productivity, sales and employment. At the regional R&D level, the central government R&D fund and firm self R&D budget will be the source of R&D investment. Further positive effects are inter-related with local industries. This study carried out an empirical analysis on the effect of R&D investment on local economies using Korean panel data after comparing international literatures. The dynamic panel estimator is used to estimate an autoregressive model with lagged dependent variable. Using the Da Silva method, mixed variance-component moving-average error process is estimated and selected. R&D investment is very important factor to improve the productivity of a region and the size of the effect is dependent on the time periods within the Korean economic history.

The Association between Social Support and the Change in Depressive Symptoms among Baby Boomer (베이비부머의 사회적 지지가 우울감 변화에 미치는 영향)

  • Song, Si Young;Jun, Hey Jung;Joo, Susanna
    • 한국노년학
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    • v.39 no.2
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    • pp.347-362
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    • 2019
  • This study aimed to investigate the association between social support and the change of depressive symptoms and its difference by gender among Korean Baby Boomer. We used the Korean Longitudinal Study of Aging (KLoSA) 5th (in 2014) and 6th waves (in 2016). Samples were Korean Baby Boomer (born 1955 to 1963) who have spouse and children(N = 1,210). Dependent variable was depressive symptoms and independent variables were four social support variables (spousal relationship satisfaction, parent-child relationship satisfaction, frequency of social contact, and number of participation groups). Interaction variables between social support and gender were also included in the model. Hierarchical regression analysis with the lagged dependent variable was performed. Results showed that the higher the satisfaction of spousal relationship and the satisfaction of parent-child relationship, the less the depressive symptoms increased. All interaction variables were not significant. These findings mean that the support from the spouse and the child is helpful in lowering depressive symptoms, and the associations between social support and depressive symptoms are not different by gender among Baby Boomer. It implies that interventions for enhancing family relationships, especially spousal relationship and parent-child relationship, may be useful to reduce depressive symptoms among Korean Baby Boomer.

A Study on Price Elasticities of mobile telephone Demand in Korea (국내 이동전화 통화수요의 요금탄력성 추정에 관한 연구)

  • Jeong, Woo-Soo;Cho, Byung-Sun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.6B
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    • pp.390-401
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    • 2007
  • This paper is to estimate and analyze the price elasticities of demand for mobile calls. We used the data for the period from January 2000 to December 2005 on a monthly basis. Data used are call minutes to mobile-originating(ML+MM), tariff for dispatch of fixed and mobile calls($P_L,P_M$), income(Y), and subscriber for mobile(N). In order to provide robust estimates of price elasticities, we have used two different econometric models. One is a Dynamic model which includes a lagged dependent variable and so can differentiate between long-un and short-run price elasticities using the Generalized Method of Moments(GMM). The other is a Box-Cox transformation model which is one of the most useful methods. Box-Cox transformation model shows that elasticity changes with the lapse of time. The results are as follow : Not including the price indices for land-originating, the estimate is overestimated otherwise. In Box-Cox transformation case, price elasticity had been steadily declining. And this result shows that mobile services had been changed necessities increasingly in Korea.

Further Examinations on the Financial Aspects of R&D Expenditure For Firms Listed on the KOSPI Stock Market (국내 KOSPI 상장기업들의 연구개발비 관련 재무적 요인 심층분석)

  • Kim, Hanjoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.4
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    • pp.446-453
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    • 2018
  • The study examines corporate research & development (R&D) expenditure in modern finance. Firms may face one of the essential issues to maintain their optimal levels of R&D expenditures in order to increase corporate profit. Accordingly, financial determinants that may influence R&D spending are statistically tested for firms listed on the KOSPI stock market during the period from 2010 to 2015. Financial determinants which may discriminate between firms in high-growth and low-growth industries are examined on a relative basis. Explanatory variables including one-period lagged R&D expenses (Lag_RD), cross-product term between the Lag_RD and type of industry (as a dummy variable), and advertising expenses (ADVERTISE) significantly influenced corporate R&D intensity. Moreover, high-growth firms in domestic capital markets showed higher Lag_RD, profitability (PROF) and foreign equity ownership (FOS) than their counterparts in low-growth sectors, whereas low-growth firms had higher market-value based leverage (MLEVER) and ADVERTISE. Overall, these results are expected to influence decision-making of firms concerning the optimal level of R&D expenditure, which may in turn enhance shareholder wealth.

Estimation of kerosene demand function using time series data (시계열 자료를 이용한 등유수요함수 추정)

  • Jeong, Dong-Won;Hwang, Byoung-Soh;Yoo, Seung-Hoon
    • Journal of Energy Engineering
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    • v.22 no.3
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    • pp.245-249
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    • 2013
  • This paper attempts to estimate the kerosene demand function in Korea over the period 1981-2012. As the kerosene demand function provides us information on the pattern of consumer's kerosene consumption, it can be usefully utilized in predicting the impact of policy variables such as kerosene price and forecasting the demand for kerosene. We apply least absolute deviations and least median squares estimation methods as a robust approach to estimating the parameters of the kerosene demand function. The results show that short-run price and income elasticities of the kerosene demand are estimated to be -0.468 and 0.409, respectively. They are statisitically significant at the 1% level. The short-run price and income elasticities portray that demand for kerosene is price- and income-inelastic. This implies that the kerosene is indispensable goods to human-being's life, thus the kerosene demand would not be promptly adjusted to responding to price and/or income change. However, long-run price and income elasticities reveal that the demand for kerosene is price- and income-elastic in the long-run.

A Study on the Relationship between Standardization and Technological Innovation: Panel Data and Canonical Correlation Analysis through the use of Standardization Data and Patent Data (표준과 기술혁신의 관계에 관한 연구: 표준 제정·보유정보와 특허정보를 이용한 패널데이터 분석 및 정준상관 분석)

  • Lee, Heesang;Kim, Sooncheon;Jeon, Yejun
    • Journal of Korea Technology Innovation Society
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    • v.19 no.3
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    • pp.465-482
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    • 2016
  • Previous researches have introduced various ways to analyze the impact of standardization on innovation while the works are not only small in number but based on interview or case study. This paper addresses the impact of standardization activities within South Korean industries on technological innovation applying an empirical analysis of standardization activities and technological innovation. Drawing on Korean Industrial Standards Classification from panel data of 2003 to 2012, we employed corresponding data of each industrial classification: Number of standards, Accumulated number of standards, Number of patents applied in Korea, Sales, Operational profit, Intangible asset, and R&D invest. In the first model, we run panel data models employing the number of patents applied in Korea as an independent variable, and the number of standards, accumulated number of standards, sales, and operational profit as dependent variables to observe industrial impacts upon the relationship between standards and patents, along with time lagged consideration. The result shows that number of standards are revealed to have a negative influence on patent applications in the year of research, and no significant effect appears for the next two years while positive effect shows up on the third year. Meanwhie, accumulated number of standards turned out to have positive effects on patent applications in Korea. This implies it takes time for innovation subjects to embrace newly established standards while having a significant amount of positive effect on technological innovation in the long term. In the second model, we use canonical correlation analysis to find industrial-wide characteristics. The result of this model is equivalent to the result of panel data analysis except in a few industries, where some industry specific characteristics appear. The implications of our results present that Korean policy makers have to take account of industrial effects on standardization to promote technological innovation.