Trade and International R&D Spillovers among OECD Countries.

• Author: Funk, Mark

Mark Funk [*]

This paper examines the relationship between trade patterns and international research-and-development (R&D) spillovers using Kao and Chiang's (1998) and Kao's (1999) recently developed panel cointegration techniques. Monte Carlo--type tests demonstrate that the choice of weights used in constructing foreign R&D stocks is informative of the spillover transmission when panel cointegration techniques are employed. However, the evidence does not support a relationship between import patterns and R&D spillovers. The relationship between export patterns and R&D spillovers is then considered. Consistent with recent theoretical models (Ben-David and Loewy 1998), the evidence suggests that exporters receive substantial R&D spillovers from their customers.

1. Introduction

   Does a country's trading partners affect its long-run growth? While many authors such as Edwards (1998) have found that relatively open economies tend to grow faster than relatively closed economies, it is less clear whether a country's trading partners affect its long-run growth. One plausible way trade partners may influence long-run growth is through the transfer of knowledge. Recent empirical work reveals an apparent link between international research spillovers and import patterns. Coe and Helpman (1995) uncover empirical evidence of a relationship between domestic productivity and import-weighted foreign research stocks. Using slightly different approaches, Coe, Helpman, and Hoffmaister (1997); Engelbrecht (1997a, b); and Lichtenberg and van Pottelsberghe de la Potterie (1998) find similar results. By linking knowledge transmission to import patterns, these results suggest that trade partners do influence long-run growth.

   However, these results have come under some criticism. Keller (1998) questions whether any of these results can be interpreted as indicating a link between knowledge flows and imports. He finds that significant international spillovers are still estimated from foreign research-and-development (R&D) stocks constructed using randomly assigned weights. He interprets this result to imply that the choice of weights is not indicative of the knowledge transmission mechanism.

   While this is an ingenious test, Keller is careful to point out that his results may be due to the time-series properties of the data. As with the other studies, Keller focuses on the long-run relationship between the nonstationary total factor productivity and R&D data series but estimates the relationship using standard OLS techniques. Kao and Chiang (1998) demonstrate that the ordinary-least-squares (OLS) estimator in a cointegrated panel is asymptotically normal but with a nonzero mean. Kao, Chiang, and Chen (1999) apply panel cointegration methods to Coe and Helpman's estimation and conclude that the evidence of a relationship between imports and research spillovers is weak.

   This paper reexamines the empirical relationship between trade and R&D spillovers using the panel cointegration techniques developed by Kao and Chiang (1998). As this paper shows, accurate estimates and inference tests of the cointegrating relationship indicate no long-run relationship between imports and international flows of knowledge, confirming Kao, Chiang, and Chen's (1999) results. Keller's experiment is reconsidered next. This paper finds that when panel cointegration techniques are employed, the choice of weights used in the construction of the foreign R&D stocks is informative. As a final contribution, this paper considers exports as an alternative transmission mechanism. Ben-David and Loewy (1998) describe how even the technological leaders may gain knowledge spillovers from their export relationships. The very strong evidence presented here supports their model. The new evidence suggests that previous studies may have overstated the role of imported inputs in international R&D spillovers while un derstating other transmission mechanisms.

   The rest of the paper proceeds as follows. Section 2 outlines a simple model of innovation and productivity growth. Section 3 discusses the nonstationary nature of the data and the recent advances in panel unit root tests and panel cointegration. A reevaluation of the relationship between randomly generated import patterns and international spillovers appears in section 4. Section 5 assesses the role of exports in transmitting international research spillovers. Section 6 concludes with a brief summary and suggestions for further research.

2. Model

   While the existence and transmission of international research spillovers plays a role in a variety of models of trade and growth, the empirical tests of international research spillovers are usually motivated by appeals to endogenous growth models, such as those in Grossman and Helpman (1991). One important feature that distinguishes the Grossman and Helpman models from other endogenous growth models is the emphasis on trade as the means of international knowledge diffusion. In the Grossman and Helpman--style models, research undertaken by profit-seeking firms results in new intermediate goods that are then used in the final-goods sector. Assuming that the intermediates are imperfect substitutes, with an elasticity of substitution in production greater than one, the final-goods producers exhibit "variety-loving" behavior and productivity in the final-goods sector will be a positive function of the number of inputs available. Since the past and present research efforts determine the number of inputs availabl e, the economy's cumulative R&D efforts--its R&D stock--determines the productivity in the final-goods sector. If trade in intermediate goods occurs, then both the domestic R&D stock and the R&D stocks of trade partners will determine domestic productivity.

   Research may also contribute to a publicly available stock of knowledge. Researchers during the innovation process may draw on the public knowledge stock as a source of technical or scientific knowledge. By increasing the stock of public knowledge, current research reduces the cost of future innovations. Moreover, domestic research may spill over to foreign economies by increasing the public stock of knowledge available to foreign researchers. The knowledge created in research may be transmitted through trade since trade increases the number of contacts by which knowledge may be exchanged. If the knowledge is transmitted largely by trade, then again a country's trade partners will impact its long-run growth.

   While Grossman and Helpman (1991; pp. 166-71) argue that both imports and exports encourage knowledge flows, the literature that has emerged has argued largely that imported intermediate goods play a central role in the transmission of knowledge. Coe and Helpman offer the first empirical test of this assumption. They pool productivity and R&D data for 22 OECD countries for the years 1971 to 1990. They then estimate the effect of foreign R&D stocks on productivity levels by OLS regression of the equation

   ln [F.sub.i] = [[alpha].sub.i] + [[alpha].sup.d]1n [S.sup.d] + [[alpha].sup.f] ln [S.sup.f], (1)

   where F is the business-sector total factor productivity, [[alpha].sub.i] is a fixed effect, [S.sup.d] is the domestic R&D stock, and [S.sup.f] is the foreign R&D stock. As is standard in the literature, the domestic R&D stock is defined as the depreciated sum of all previous domestic research. The foreign R&D stock is defined as the weighted sum of the domestic R&D stocks of all other sampled nations:

   [[S.sup.f].sub.i] = [[[sigma].sup.k].sub.j=1] [m.sub.i,j][[S.sup.d].sub.j],

   where the weight [m.sub.ij] in this case is the bilateral import share, that is, the volume of imports to country i from country j divided by the total imports to i from all nations in the sample. By adjusting the contribution of foreign R&D to the foreign knowledge stock, the weights reflect preconceptions of the knowledge sources and recipients, the proportion of knowledge that is spillable, and the channels of knowledge diffusion. [1] As such, the weights may reflect the geographic, technological, or economic distance between the research performer and the spillover recipient. Coe and Helpman's definition of the foreign R&D stock assumes that knowledge flows through imports.

   The argument that imports are the primary method of international knowledge diffusion raises a few questions. Grossman and Helpman (1991, pp. 166-7) suggest two reasons why bilateral import shares may be correlated with international research spillovers: Bilateral import shares are a proxy for contacts between residents and firms residing in different nations, and the knowledge embodied in imported intermediate...