Spatial Dependence of Technology Spillovers among Trading Partners
-
Fadi Fawaz
und
Mashaallah Rahnama Moghadam
Abstract: Previous literature suggests that trade contributes to knowledge and technology spillovers among trading partners. Using panel data and country-specific fixed effects, we show that the technology of a country is explained by existing technology of its major trading partners. We build an endogenous growth model for OECD countries for the 1960–2010 period; we draw the residuals to measure the Total Factor Productivity (TFP) of each country. Then, using spatial econometrics, we regress the TFP of each country on previous TFP of its major trading partners. In addition, we run a Random Coefficient Model, to let this relationship vary randomly by country. Finally, we run the endogenous growth model again, but now it includes the spatial lag term as an explanatory variable.
References
Anselin, Luc.1988. Spatial Econometrics: Methods and Models.Kluwer Academic Publishers, Boston, MA.10.1007/978-94-015-7799-1Suche in Google Scholar
Baltagi, Badi. 2001. Econometric Analysis of Panel Data. Second edition. Wiley, New York, NY.Suche in Google Scholar
Beck, Nathaniel, Kristian S.Gleditsch, and KyleBeardsley. 2006. “Space Is More Than Geography: Using Spatial Econometrics in the Study of Political Economy.” International Studies Quarterly50:27–44.10.1111/j.1468-2478.2006.00391.xSuche in Google Scholar
Beck, Nathaniel and Jonathan N.Katz2007, “Random Coefficient Models for Time-Series-Cross-Section Data: Monte Carlo Experiments,” Political Analysis 15:182–195.10.1093/pan/mpl001Suche in Google Scholar
Coe, David T., and ElhananHelpman. 1995. “International R&D Spillovers.” European Economic Review39(5):859–887.10.1016/0014-2921(94)00100-ESuche in Google Scholar
Coe, David T., and ElhananHelpman, and Alexander W.Hoffmaister. 1997. “North-South R&D Spillovers.” The Economic Journal107(440):134–149.10.1111/1468-0297.00146Suche in Google Scholar
Falvey, Rod, and NeilFoster, and DavidGreenaway. 2004. “Imports, Exports, Knowledge Spillovers and Growth.” Economic Letters85:209–213.10.1016/j.econlet.2004.04.007Suche in Google Scholar
Gleditsch, Kristian S.2002. “Expanded Trade and GDP Data.” Journal of Conflict Resolutions46:712–714.10.1177/0022002702046005006Suche in Google Scholar
Grossman, Gene, and ElhananHelpman. 1991. “Trade, Knowledge Spillovers and Growth.” European Economic Review35:517–526.10.1016/0014-2921(91)90153-ASuche in Google Scholar
Hsiao, Cheng. 1986. Analysis of Panel Data.” Cambridge University Press, Cambridge, United Kingdom.Suche in Google Scholar
International Monetary Fund. 2012. Direction of Trade Statistics.Suche in Google Scholar
Nickel, Stephen. 1981. “Biases in Dynamic Models with Fixed Effects.” Econometrica49(6):1417–1426.10.2307/1911408Suche in Google Scholar
Weinhold, Diana. 2002. “The Importance of Trade and Geography in the Pattern of Spatial Dependence of Growth Rates.” Review of Development Economics6(3):369–382.10.1111/1467-9361.00161Suche in Google Scholar
- 1
As we will see later, research following Grossman et al. (1991) does suggest different channels through which spillover effects take place.
- 2
As stated in this article, only a few years ago Grossman et al. (1991) had address the lack of literature addressing the channels through which spillover effects take place.
- 3
As I explain in the following section, the introduction of a lagged dependent variable in dynamic panel data results in biased coefficients (Nickel, 1981). Falvey et al. chose Arellano and Bond’s GMM procedure (1991). In this essay we have chosen to use an instrumental variable (IV) method suggested by Hsiao (1986).
- 4
See Weinhold (2002).
- 5
In fact, it is an instrument for investment. A more detailed explanation on how this instrument was created is presented in the following section.
- 6
Limiting to three trading partners allows us to have values for TFP of these countries. As the number of partners increases, it is likely to have a great number of missing observations in the weighting matrix.
- 7
It is the same Instrumental variable Method used in the construction of the Growth Model. For a more detailed explanation, see “The Endogenous Growth Model Section” in this article.
- 8
See Coe et al. (1997).
© 2013 by Walter de Gruyter Berlin / Boston
Artikel in diesem Heft
- Article
- Industrial and Agricultural Pollution Patterns
- Is Food Security a New Tariff? Explaining Changes in Sanitary and Phytosanitary Regulations by World Trade Organization Members
- Spatial Dependence of Technology Spillovers among Trading Partners
- What’s News
- Surmounting the Individual: Establishing a Common Currency in Asia – A Case Study of East Asian Economies
- Pre-conditions for Inflation Targeting in an Emerging Economy: The Case of India
- Exchange Rate Pass-Through into Import Prices in Jordan
- The Globalization of the Australian Textile, Clothing, Footwear and Motor Vehicle Industries: Results in Line with Other Western Market Economies
Artikel in diesem Heft
- Article
- Industrial and Agricultural Pollution Patterns
- Is Food Security a New Tariff? Explaining Changes in Sanitary and Phytosanitary Regulations by World Trade Organization Members
- Spatial Dependence of Technology Spillovers among Trading Partners
- What’s News
- Surmounting the Individual: Establishing a Common Currency in Asia – A Case Study of East Asian Economies
- Pre-conditions for Inflation Targeting in an Emerging Economy: The Case of India
- Exchange Rate Pass-Through into Import Prices in Jordan
- The Globalization of the Australian Textile, Clothing, Footwear and Motor Vehicle Industries: Results in Line with Other Western Market Economies
