Export Competitiveness and Technological Capability in Bioenergy Sector
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
This paper tests the dynamic relationship between each country's export comparative advantage and technological capability in bioenergy technology sector using panel data from 20 OECD countries over the period from 1993 to 2008. The study implements heterogeneous panel unit root tests and cointegration tests, taking the normality and cross-section dependence test into account. The study finds evidence that there is co-movement among the series. Thus, the empirical model to test the casual relationship among the variables in question is based on the panel VECM model and implements panel GMM estimation to determine the dynamic relationships between the series to deal with a simultaneity problem introduced by difference and existence of heteroscedasticity in the genuine errors across industries. The long-run relationship emerging from the DOLS results indicates that 1 unit increase in technological capability increases trade comparative advantage by some 2.3 unit. The RSCA and CO2PC variables respond to a deviation from the long-run equilibrium in the previous period. In the causality results, this study finds evidence of a positive short-run and strong linear causal relation running from RSCA to TSCA, and a positive strong linear causal relation running for TSCA to RSCA.
Abstract
This paper tests the dynamic relationship between each country's export comparative advantage and technological capability in bioenergy technology sector using panel data from 20 OECD countries over the period from 1993 to 2008. The study implements heterogeneous panel unit root tests and cointegration tests, taking the normality and cross-section dependence test into account. The study finds evidence that there is co-movement among the series. Thus, the empirical model to test the casual relationship among the variables in question is based on the panel VECM model and implements panel GMM estimation to determine the dynamic relationships between the series to deal with a simultaneity problem introduced by difference and existence of heteroscedasticity in the genuine errors across industries. The long-run relationship emerging from the DOLS results indicates that 1 unit increase in technological capability increases trade comparative advantage by some 2.3 unit. The RSCA and CO2PC variables respond to a deviation from the long-run equilibrium in the previous period. In the causality results, this study finds evidence of a positive short-run and strong linear causal relation running from RSCA to TSCA, and a positive strong linear causal relation running for TSCA to RSCA.
참고문헌 (31)
- Amable, B., "The role of technology in market shares dynamics", Applied Economics, 27, pp.197~204 (1995)
- Amendola, G., "Trade, growth and technological change", pp.141~167 (1998), Cambridge University Press
- Arellano, M., "Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations", Review of Economic Studies, 58, pp.277~297 (1991)
- Arent, D. J., "The status and prospects of renewable energy for combating global warming", Energy Economics, 33, pp.584~593 (2011)
- Dalum, B., "Structural changed in OECD export specializations: de-specialization and ‘stickiness’", International Review of Applied Economics, 12, pp.423~443 (1998)
- Cointegration in panel data with breaks and cross-section dependence, "Banerjee, A.", European Central Bank, ~, pp.Working Paper 591. (2006)
- Banerjee, A., "Some cautions of the use of panel methods for integrated series of macro-economic data", Econometrics Journal, 7(2), pp.322~340 (2004)
- Breitung, J., "roots and cointegration in panels, In The econometrics of panel data: Fundamentals and recent developments in theory and practice", pp.297~322 (2008), Kluwer Academic Publishers
- Dosi, G., "The economics of technological change and international trade" (1990), Harvester Wheatsheaf
- Frees, E. W, "Assessing cross-sectional correlation in panel data", Journal of Econometrics, 69, pp.393~414 (1995)
- Grupp, H., "Trade on high-technology markets and patent statistics-leading-edge versus high-level technology, In Trade, growth and technological change", pp.168~187 (1998), Cambridge University Press
- Hansen, L, "Large sample properties of generalized method of moment estimators", Econometrica, 50, pp.1029~1054 (1982)
- Holtz-Eakin, D., "Estimating vector autoregressions with panel data", Econometrica, 56, pp.1371~1395 (1998)
- Im, K. S., "Testing for unit roots in heterogeneous panels", Econometrica, 115, pp.53~74 (2003)
- Trade flows, barriers and market drivers in renewable energy supply goods: The need to level the playing field, "Jha, V.", International Centre for Trade and Sustainable Development, ~, pp.ICTSD Trade and Environment Issue Pape 10 (2009)
- Johnstone, N., "Renewable energy policies and technological innovation: Evidence based on patent counts", Environmental and Resource Economics, 45, pp.133~155 (2010)
- Kao, C., "On the estimation and inference of a cointegrated regression in panel data", Advances in Econometrics, 15, pp.179~222 (2000)
- Revealed comparative advantage and alternatives as measures of specialization, "Larsen, K.", Danish Research Unit for Industrial Dynamics, ~, pp.Working Paper. No. 98-30 (1998)
- Laursen, K, "Do export and technological specialization patterns co-evolve in terms of convergence or divergence? Evidence from 19 OECD countries, 1971-991", Journal of Evolutionary Economics, 10, pp.415~436 (2000)
- Lund, P. D, "Effects of energy policies on industry expansion in renewable energy", Renewable Energy, 34, pp.53~64 (2009)
- Pedroni, P., "Critical values for cointegration tests in heterogeneous panels with multiple regressors", Oxford Bulletin of Economics and Statistics, (Special Issue), pp.653~678 (1999)
- Pedroni, P, "Fully modified OLS for the heterogeneous cointegrated panels", Advances in Econometrics, 15, pp.93~130 (2000)
- Pedroni, P, "Panel cointegration: Asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis", Econometric Theory, 20, pp.597~625 (2004)
- Pesaran, H. M, "A simple panel unit root test in the presence of cross-section dependence", Journal of Applied Econometrics, 22, pp.265~312 (2007)
- General diagnostic tests for cross section dependence in panels, "Pesaran, M. H.", University of Cambridge, ~, pp.Cambridge Working Papers in Economics. No. 0435 (2004)
- Pesaran, M. H., "Pooled mean group estimation of dynamic heterogeneous panels", Journal of the American Statistical Association, 94(446), pp.621~634 (1999)
- Roodman, D, "How to extabond 2: An introduction to difference and system GMM in Stata", The Stata Journal, 9, pp.86~136 (2009)
- Saikkonen, P, "Asymptotically efficient estimation of cointegration regressions", Econometric Theory, 12(1), pp.1~21 (1991)
- Sargan, J., "The estimation of economic relationships using instrumental variable", Econometrica, 26, pp.393~415 (1958)
- Uchida, Y., "The transformation of competitive advantage in East Asia: An analysis of technological and trade specialization", World Development, 33, pp.701~728 (2005)
- Westerlund, J, "Testing for error correction in panel data", Oxford Bulletin of Economics and Statistics, 69, pp.709~748 (2007)