• Journal of Korea Technology Innovation Society
• /
• v.11 no.1
• /
• pp.72-90
• /
• 2008

What has been the contribution of industrial innovation to economic growth? Typically, the issue has been approached with growth-accounting methods augmented to include a "stock of knowledge". An independent estimate of the rate of return to R&D is found in order to impute patents granted to the accumulation of knowledge. Griliches(1973) then uses a regression approach to assess the effect of an R&D variable on the computed TFP growth rate. The regression coefficient on the R&D variable would provide an estimate of the social rate of return to R&D. The related studies tend to show high social rates of return to R&D, typically in a range of 20 to 40 % per year. We need to provide multiple equation dynamic system for productivity and innovation in Korean economy in state space form. A wide range of time series models, including the classical linear regression model, can be written and estimated as special cases of a state space specification. State space models have been applied in the econometrics literature to model unobserved variables like productivity. Estimation produces the following results. Considering the goodness of fit, we can see that the evidence is strongly in favor of the range $0.120{\sim}0.135$ for the elasticity of TFP to R&D stock in the period between 1970's and the early 2000's.

• Proceedings of the Technology Innovation Conference
• /
• 2001.06a
• /
• pp.145-156
• /
• 2001

This paper investigates the effect of imported technology on the economic growth of Korea. To this end, the relationship between input technology and economic growth are suggested in the numerical form and analysed empirically. The rates of return of technology investments, which are divided into the domestic R&D investment and the investment on imported technology, are estimated. Based on the result of this analysis, the rate of return of the input technology, which includes the domestic R&D investment and the investment on imported technology, are estimated as 31.4%, and this input technology is calculated as to contribute 8.9% on the economic growth rate of Korea. And the domestic R&D investment is fumed out to have bigger rate of return than the investment on imported technology during the surveyed period. However, the rates of return of detailed R&D investments, which can be divided into the investments on commercial R&D and basic science, were not calculated in this paper, because of the lack of data on this in this paper. As well, the time-lag effect, which is naturally believed to exist between the R&D investment and the economic growth, could not be analysed wit:1 the same reason. Thus when analysing the relationship between them, this paper tried to minimize the time-lag effect by using the long-term data of twenty-three years.

• KDI Journal of Economic Policy
• /
• v.27 no.1
• /
• pp.81-122
• /
• 2005

The paper aims to establish the characteristics of the Korean firms' R&D investment and to estimate the private rate of return to R&D investment. For the empirical analysis, a balanced panel data is constructed with 695 firms on 8 year observations. The panel data enables to characterize R&D investment of the Korean firms, which is mostly conformed to the 'stylized facts' of R&D investment that found in the previous studies on foreign firms. Klette model was used to estimate the private rate of return on R&D investment and depreciation rate of R&D capital. The paper estimates that the rate of return on R&D investment is 10.5% on average or 16.4% on median for the whole industry whereas manufacturing firms show 10.4% on average or 16.4% on median. The depreciation rate was estimated about 32.9% for whole industry, where it ranges from the minimum 11.6% for metal industry and 49.5% for services. The median estimate of the rate of return for R&D investment of Korean firms is roughly two times higher than real interest rates for the same period, which implies that R&D investment allows sizable rent in addition to the opportunity cost of capital investment.

• Journal of Korea Technology Innovation Society
• /
• v.7 no.2
• /
• pp.325-349
• /
• 2004

This paper tried to evaluate an economic analysis about research and development far areas of renewable resource in Korea. To evaluate this validity, we tried to calculate the spillover effect of R＆D investment through input-output table. In the first stage of spillover effect, we simply calculate the rate of return on R＆D investment for renewable energy resources in Korea through the input-output model, which can calculate the value added as well as output based upon the price of 2000 year. According to the first stage calculation, the rate of return on R＆B investment in solar heat is higher than any other renewable energy. In the second stage we tried to calculate the second round of spill over effect, which derives from the additional amount of supply of renewable resources due to the R＆D investment. The overall evaluation of R＆D invesment including the first stage as well as second stage spillover effect shows that bio-energy and waste energy generate 14 times as well as 2.5 times in the rate of return respectively.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.40 no.1
• /
• pp.50-56
• /
• 2017

The IRR (internal rate of return) is often used by investors for the evaluation of engineering projects. Unfortunately, it is widely known that it has serial flaws. Also, External rate of returns (ERRs) such as ARR (Average Rate of Return) or MIRR (MIRR, Modified Internal Rate of Return) do not differentiate between the real investment and the expenditure. The PRR (Productive rate of return) is faithful to the conception of the return on investment. The PRR uses the effective investment instead of the initial investment. In this paper, we examined two cases of the engineering project. the one is a traditional engineering project with financing activity, another is the project with R&D. Although the IRR has only one value, it overestimates or underestimate profitabilities of Engineering Projects. The ARR and the MARR assume that a returned cash reinvest other projects or assets instead of the project currently executing. Thus they are only one value of a project's profitability, unlike the IRR. But the ARR does not classify into the effective investment and non-investment expenditure. It only accepts an initial expenditure as for an investment. The MIRR also fails to classify into the investment and the expenditure. It has an error of making a loss down as the investment. The IRR works as efficiently as a NPW (Net Present Worth). It clearly expresses a rate of return in respect of an investment in an engineering project with a loan. And it shows its ability in an engineering project with a R&D investment.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.20 no.44
• /
• pp.129-134
• /
• 1997

The purpose of this study is to estimate the distribution rate of R&D input on R&D output in major manufacturing industrial sector. The distribution rate is estimated on time-series data for the period 1980 to 1996. The data used in this study can be divided into the two categories. 1) R&D output data (Patent, Utility) 2) R&D input data (R&D expenditure, R&D workers) The raw data of R&D expenditure is transformed into R&D stock. And the specific production function is used to represent the interaction between R&D input and output. The production function shows the maximum rate of R&D output that can be achieved by certain given, technologically possible, R&D input combinations. The main findings can be summarized as follows. 1) There was a diminishing return between R&D input and output$(\alpha+\beta<1). 2) R&D output growth was more affected by R&D expenditures than R&D workers. 3) R&D workers were more contributed highly to Patent granted than Utility model.

• Proceedings of the Korea Technology Innovation Society Conference
• /
• 2000.11a
• /
• pp.346-356
• /
• 2000

This paper aims to analyse the relationship between R＆D investment and economic growth in Korea. The analysis result shows 38 percent of average economic growth rate(7.1%) of Korea between 1976 and 1998 was achieved by the growth of Total Factor Productivity (TFP), and the R&D investment during the period contributed in achieving the economic growth rate by as much as 9.86 percent. In the process of the estimate, the rate of return of the R&D investment from both government and private was calculated as 47 percent. The relationship between private R&D investment, government R&D investment and the GDP was also investigated, and it was estimated that the private sector invested 2.0 percent of the GDP in R&D during the period, and was found that 1 won of government R&D investment induced 0.202 won of private sector's R&D investment. However, the time-lag effect, which is naturally believed to exist between the R&D investment and the economic growth, could not be analysed in a mathematical form, because of the lack of the data to establish this relationship. However, this paper believe that the time-lag effect in this relationship was included implicitly by using the data of 23 years.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.4
• /
• pp.695-703
• /
• 2016

The maintenance method for the electrical facility of high speed railway has been evolved from inspection by personnel to the automated way by the detection devices. In particular, the signalling equipment in order to increase the safe and efficient operation of the trains is required to maintain normal operation by periodic maintenance. Because the return current gives the most important effects to the wayside equipment in case of the failures, a method is needed to measure the unbalanced rate of return current on the train at high speed driving. The Hot Box Detector(HBD) device that is installed at track-side has a function to recognize the abnormal axle box by detecting the temperature that occurs in the axle of train passing over its device. In order to implement the measurement equipment for unbalanced rate of return current and axle temperature, the design method is proposed and the experimental test results by test bed are included in the paper.

• Clinics in Shoulder and Elbow
• /
• v.26 no.2
• /
• pp.109-116
• /
• 2023

Background: Golf is a popular sport involving overhead activity and engagement of the rotator cuff (RC). This study aimed to determine to what level golfers were able to return to golf following RC repair, the barriers to them returning to golf and factors associated with their failure to return to golf. Methods: Patients preoperatively identifying as golfers undergoing RC repair at the study centre from 2012 to 2020 were retrospectively followed up with to assess their golf-playing status, performance and frequency of play and functional and quality of life (QoL) outcomes. Results: Forty-seven golfers (40 men [85.1%] and 7 women [14.9%]) with a mean age of 56.8 years met the inclusion criteria, and 80.1% were followed up with at a mean of 27.1 months postoperatively. Twenty-nine patients (76.3%) had returned to golf with a mean handicap change of +1.0 (P=0.291). Golf frequency decreased from a mean of 1.8 rounds per week preinjury to 1.5 rounds per week postoperatively (P=0.052). The EuroQol 5-dimension 5-level (EQ-5D-5L) index and visual analog scale (EQ-VAS) score were significantly greater in those returning to golf (P=0.024 and P=0.002), although functional outcome measures were not significantly different. The primary barriers to return were ipsilateral shoulder dysfunction (78%) and loss of the habit of play (22%). Conclusions: Golfers were likely (76%) to return to golf following RC repair, including mostly to their premorbid performance level with little residual symptomatology. Return to golf was associated with a greater QoL. Persistent subjective shoulder dysfunction (78%) was the most common barrier to returning to golf.

• The Journal of Fisheries Business Administration
• /
• v.44 no.2
• /
• pp.101-109
• /
• 2013

This study is aimed to analyze investment effects of fisheries R&D projects of the National Fisheries Research and Development Institute(NFRDI). In the analysis, Granger causal relations between R&D investment and fisheries production are tested. In addition, time-lag effects of fisheries R&D investment are estimated with an impulse response analysis and investment effects of R&D projects are estimated by changes of social surplus. Results indicate that there exists an Granger-causality between R&D investment and fisheries production and fisheries production responds to the fisheries R&D shock about three years after the initial shock. The magnitudes of the impacts increase until a peak is reached 5~7 years and the impacts decline to zero after 25 years. As investment effects, it is shown that the internal rate of returns of fisheries R&D investment is 55.2%.