اثر ناهمگن هزینه R & D فناوری پیشرفته صنعتی بر رشد اقتصادی
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|17221||2013||4 صفحه PDF||سفارش دهید|
نسخه انگلیسی مقاله همین الان قابل دانلود است.
هزینه ترجمه مقاله بر اساس تعداد کلمات مقاله انگلیسی محاسبه می شود.
این مقاله تقریباً شامل 2800 کلمه می باشد.
هزینه ترجمه مقاله توسط مترجمان با تجربه، طبق جدول زیر محاسبه می شود:
|شرح||تعرفه ترجمه||زمان تحویل||جمع هزینه|
|ترجمه تخصصی - سرعت عادی||هر کلمه 90 تومان||7 روز بعد از پرداخت||252,000 تومان|
|ترجمه تخصصی - سرعت فوری||هر کلمه 180 تومان||4 روز بعد از پرداخت||504,000 تومان|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Business Research, Volume 66, Issue 10, October 2013, Pages 1990–1993
Empirical evidence has suggested that R&D investment is positively related to economic growth. This paper extends prior research by further examining the heterogeneous effects of R&D expenditures in the high-tech sector on economic growth. This study adopts a quantile regression approach to explore the marginal effect of R&D expenditures in the high-tech sector across different quantiles of the conditional GDP distribution for 23 OECD countries and Taiwan during 1991–2006. Empirical evidences show that the impacts of R&D expenditures in the high-tech sector are heterogeneous across levels of per capita income. High-tech industrial R&D spending has a strong positive effect on GDP per capita at the highest quantile of the distribution. However, all sectors' R&D spending relative to GDP is subject to significant negative returns only when considering the middle income countries. The study provides a more comprehensive understanding of the correlation between R&D investment and economic growth.
R&D is a key measure of innovation activities and is an important source of productivity growth (Griliches, 1981 and Stokey, 1995). An extensive literature (Aghion and Howitt, 1992, Cameron, 1996, Grossman and Helpman, 1991 and Romer, 1990) supports the conclusion that investments in research and development (R&D) are crucial for economic growth. Jones and Williams, 1998 and Jones and Williams, 2000 find that socially optimal R&D investment greatly exceeds actual level. Accordingly, many governments have vastly increased their economic and policy commitments to innovation with significant impacts on levels of R&D expenditures of their countries (Furman & Hayes, 2004). Although previous studies suggest a positive correlation between the level of investment in R&D and economic growth, Jones, 1995 and Jones, 1998 and Jones and Williams (2000) argue that the negative duplication externality from firms' competition and the creative destruction from the redistribution of innovators' rents may make the measured aggregate contribution of R&D to economic growth very uncertain. Pessoa (2010) shows that innovation policy has frequently relied on a ‘linear model’ of the impact of science and technology on economic development, which is often empirically supported on the positive correlation between R&D intensity and total factor productivity (TFP) growth. However, a spurious, positive relationship may be found if some factors omitted in the typical regressions. The problem of using the OLS regression analysis for the R&D based endogenous growth model is that the model implicitly assumes that the elasticity of output with respect to R&D is constant through time or across firms. Ulku (2004) shows that there is no evidence for constant returns to innovation in terms of R&D, implying that innovation does not lead to permanent increases in economic growth. This raises questions about the capacity of developed and developing countries to translate their technological innovations into productivity and economic growth. Economic development may become unsustainable in the long run as the innovation process is nonlinear and multidirectional (Dodgson, 2000, Pavitt, 2005 and Rothwell, 1994). Since the mid-90s, along with the information technology revolution, high-tech industry is playing a key role in promoting economic development. And, the innovation is regarded as a major force in developing the positive relationship between high-technology goods and economic growth (Lichtenberg, 1992). Griliches and Mairesse (1984), Nadiri (1993), Tsai and Wang (2004), and Ortega-Argilés, Piva, Potters, and Vivarelli (2010) suggest that R&D expenditures in the high-tech industries generate higher economic growth compared with R&D in other industries. Hill (2002) shows that the development of high-tech industry in the United States, Western Europe, Japan, and the newly industrialized economies (NIEs) of East Asia, including Taiwan, has contributed greatly to their national economic growth over the last decade. Technological opportunities and appropriability conditions are so different across sectors and countries (Aghion and Howitt, 1996, Dosi, 1997 and Greenhalgh et al., 2001). This suggests the possibility of differences in the sector/country specific R&D productivity links. As an alternative to OLS regression, this study uses quantile regression to examine the heterogeneous effects of R&D spending in the high-tech sector on economic growth for the sample of OECD countries and Taiwan over the period 1991–2006. The quantile regression analysis allows researchers to estimate covariate effects at different points of the distribution. Therefore, the empirical and methodological contribution of this paper is to help determine whether the high-tech R&D elasticities are different across countries. The remainder of the paper is organized as follows. Section 2 introduces the research methodology and the model. Section 3 presents the empirical results. Section 4 contains a discussion and conclusion.
نتیجه گیری انگلیسی
In order to re-interpret the relationship between high-tech R&D and economic growth, this paper uses quantile regression method and a sample data set of OECD countries and Taiwan over the period 1991–2006. The findings show that Ordinary Least Square estimates are potentially misleading because they fail to capture how high-tech R&D expenditures shape economic growth when focusing on the entire income distribution. Unlike OLS estimates, the quantile approach shows that high-tech R&D in general has no statistically significant positive impact on economic growth. Yet the quantile approach adds to the story by revealing that such an effect is conditional on the position the country occupies in the income distribution. Using quantile regression, this research finds that the positive effect of high-tech R&D spending on income is especially evident when considering the extreme upper quantile. For low and middle income countries, an additional high-tech R&D investment does not affect significantly the economic growth of the countries. The findings could have policy implications that high-tech R&D investment is most effective for countries with the highest per capita income. The variable of all sectors' R&D spending relative to GDP is subject to significant negative returns only when considering the middle income countries. The lack of significant effects of total business sector R&D expenditures at the other countries suggests the existence of thresholds in the degree of income of a country. Our empirical findings on the R&D-based growth model, as a whole, have derived important policy implications that only the high-tech R&D spending in the highest per capita income country can give a big boost to economy and other types of R&D expenditures seem to play no role in a country's economic development. This study introduces the quantile regression approach to the growth model and has revealed new insights into the role of high-tech R&D investment in economic development. The paper has advanced the literature by demonstrating the importance of model selection when attempting to detect the nonlinear relationship between high-tech R&D investment and economic development. The findings would provide valuable guidance for both researchers and policymakers on the growth-enhancing effects of R&D investment.