Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
International Knowledge Spillovers and Wage Inequality in Developing Countries Ming-cheng Wang, Chen-ray Fang and Li-hsuan Huang 12/02/2008 Abstract In this paper, international knowledge spillovers are incorporated in a horizontal innovation model, designed to explain the observed uncertain effects that openness of trade can have on wage inequality in small developing countries. Openness of trade can produce two different effects: an increase in the relative price of less-skilled labor-intensive products and a wider skill discrepancy due to knowledge spillovers from the more to less developed country. The former triggers a fall in the wage premium, while the latter widens the wage premium gap in the developing country. These two opposing forces explain the observed uncertain effects of openness to trade on wage inequality in developing countries. JEL Clasification: F110, F430, J310, O300, O410. Keywords: international knowledge spillovers, wage inequality, developing country, endogenous growth model Ming-cheng Wang, Associate Professor, Department of Economics, National Central University, Chungli 320, Taiwan, R.O.C. Tel.: 011-886-3-4227151 ext. 66307, E-mail: [email protected]. Chen-ray Fang, Associate Professor, Department of Economics, National Taipei University, 151, University Rd., San Shia, Taipei, 237, Taiwan, R.O.C. Tel.: 011-886-2-86747132, Fax: 011-886-2-26739880, E-mail: [email protected]. Corresponding author. Li-hsuan Huang, Professor, Department of Economics, National Central University, Chungli 320, Taiwan, R.O.C. Tel.: 011-886-3-4227151 ext. 66306, Fax: 011-886-3-4222876 E-mail: [email protected]. 1. Introduction The conventional Stolper-Samuelson theorem in the trade literature1 predicts that openness of trade will lead to a decrease in wage premium in a country if it is relatively unskilled-labor abundant. Increased openness should lead to less wage inequality in developing countries where less-skilled labor is often relatively abundant. The empirical evidence for this prediction is however mixed. Despite the fact that increased openness did lead to a decrease in wage inequality in the 1960s in Taiwan and South Korea and in the 1970s in Singapore [Robbins (1996); and Wood (1996)], this was not the case in some of the Latin American countries in the 1980s and 1990s.2 We can thus find different evidence of the effects of openness on wage inequality in developing countries. The Stolper-Samuelson mechanism seems to ignore factors that increase wage inequality when developing countries open up to trade. This leaves space for theorists to fill the void and look for theoretical models that are capable of explaining the above diverse wage inequality movements. In the literature, studies on determination of the wage inequality between skilled labor and less-skilled labor either generally focus on developed countries or neglect certain trade issues [Aghion, Caroli and Garcia-Penalosa (1999); Galor and Moav (2000); Aghion (2002) and Acemoglu (2002); Fang, Huang and Wang (2008)].3 Until recently, one line of trade research has focused in particular on explaining the wage inequality in developing countries. In these studies, a variety of mechanisms are proposed to model the impact of trade openness on the observed diverse wage inequality movements in developing countries such as outsourcing [Feenstra and Hanson (1996)], nontraded goods 1 It refers to the restrictive version of the Stolper-Samuelson theorem in Deardroff (1994). For instance, as cited in Zhu and Trefler (2005), just over half of 20 developing and newly industrialized countries in the Freeman and Oostendorp (2001) wage database experienced rising wage inequality throughout the 1990s. 3 For instance, Acemoglu (2002) develops a model that stresses the market size effect and the endogenous technology choice, reaching the conclusion that increased openness leads to an increase in wage inequality in the northern countries. 2 1 with tariff reductions [Xu (2003)], preference heterogeneity [Glazer and Ranjan (2003)], product cycles with exogenous northern (developed country) innovations [Zhu (2004)], southern (developing country) catch-up [Zhu and Trefler (2005)] ,4 trade fragmentation [Marjit, Beladi and Chakrabarti (2004)], and differences in trade policies before trade liberalization [Ripoll (2005)].5 In this study we examine the above issue but offer a different mechanism. We incorporate both international knowledge spillovers (hereafter IKS) and intra-national (sectoral) knowledge spillovers into Romer’s (1990) horizontal innovation model. Incorporating sectoral knowledge spillovers is common in a two-sector model setup6. The justifications for incorporating IKS into the north-south trade model are twofold. First, empirical evidence for knowledge spillovers from developed countries to developing countries is significant. Coe and Helpman (1995) and Lichtenberg and Potterie (1998) consider that international R&D expenditure significantly enhances total factor productivity; the effects are more profound with the degree of the openness. Moreover, Coe, Helpman and Hoffmaister (1997) document that 1% of R&D expenditure in developed countries raised productivity in developing countries by 0.06%.7 Second, recent theories of economic growth identify trade as a major vehicle for IKS, which makes available to the developing country products that embody foreign knowledge, 4 Unlike Zhu and Trefler (2005), the innovation rate is endogenous in our model. Fischer (2001), Beaulieu, Benarroch and Gaisford (2004) and Long, Riezman and Soubeyran (2004) provide other explanations. Fischer (2001), for example, uses a dynamic specific factors model to explain the income inequality following trade liberalization and concludes that income inequalities in land (labor)-abundant countries increase (decrease) dynamically after trade liberalization. 6 See Fang, Huang, and Wang (2008) for examples of the sectoral spillover: the space-age technology of visco-elastic foam used in manufacturing memory foam pillows and beds to promote good quality sleep; and the medical lab-technology used in cosmetics services. The presence of sectoral knowledge spillover is also evident as shown in empirical studies by Bernstein and Nadiri (1988), Griliches (1992), Branstetter (2001), and Keller (2002). 7 Engelbrecht (2002) utilizes data from 77 developing countries to confirm the positive role of human capital in the absorption of international knowledge spillovers. Bernstain and Mohnen (1998) and Branstetter (2001) documents that international knowledge spillover exists in firm level data. 5 2 thereby enhancing productivity.8 It is also likely to open communication channels that stimulate the adoption of foreign ideas. The main purpose of this paper is thus to propose a theoretical framework, incorporating trade and international knowledge spillovers, that is capable of predicting the above-mentioned uncertain effects of openness on wage inequality in developing countries. The logic is straightforward. On the one hand, openness of trade facilitates IKS, which in turn increases the relative demand for skilled labor and pushes up wage inequality in developing countries. New technologies obtained by the skilled (in the developing countries) will to some extent diffuse to less skilled workers thereby leading to an increase in the demand for less-skilled labor. The net effect of these two kinds of knowledge spillovers on the equilibrium wage inequality in the developing country is herein referred as the skill discrepancy effect. On the other hand, in a country that is relatively unskilled-labor abundant, openness of trade can lead to a decrease in wage premium, which we refer as the price effect. These two opposing effects can both affect wage inequality in a small developing country after it has been opened to trade. If it is, in fact, the relative strength of the above two forces that determines wage inequality in small developing countries, then the effect of increased trade openness on wage inequality could vary at different time periods and in different countries. Since it is plausible that the effect of IKS was larger in the 1980s than in the 1960s, we interpret the widening of wage inequality that occurred in some Latin American countries (for example: from the mid-1970s to the early 1980s in Argentina and Chile; between the mid-1980s and the mid-1990s in Colombia, Costa Rica and Uruguay; from 1984 to 1990 in Mexico [Zhu and Trefler (2005)]) was a result of the dominance of the skill 8 Grossman and Helpman (1991), Chuang (1997), Murat and Pigliaru (1998) and Ben-David and Loewy (2000) incorporate international knowledge spillovers into theoretical models to examine the relationship between trade and growth. These models, however, consider only one type of labor and are therefore unable to examine the effects of the increased openness on wage inequality in developing countries. 3 discrepancy effect, while the declining wage inequality in Taiwan and South Korea, after trade was opened up in the 1960s, was a result of the dominance of the price effect. Our proposed model can thus explain diverse wage inequality movements in the empirical evidence in developing countries that have been opened up to trade. This complements the explanation of the southern wage inequality mentioned in the literature above. The remainder of the paper is organized as follows. In Section 2 we outline the model for determining wage inequality under free trade. The home country is specified as being a small country, with a relative abundance of less-skilled labor. International knowledge spillovers are built into the R&D sectors. In Section 3 we compare results for the international trade regime with those under autarky. In the final section some conclusions are offered. 2. The Model Consider an economy, endowed with less-skilled denoted by L and skilled labor H , which produces two final goods, traditional goods X and advanced goods Y. Both types of labor are either combined with specific capital goods to produce final goods or hired by R&D firms to design blueprints to produce the associated capital goods. Specific factors are utilized to produce both types of final goods, in the sense that the traditional final goods are produced by less-skilled labor and the capital goods that are associated with this less-skilled labor; the advanced final goods likewise. In the same vein as in the final goods sectors, specific labor is hired to produce blueprints in the two R&D sectors. Less-skilled labor is the sole input in the traditional R&D sector, while skilled labor is the only input for the advanced R&D sector. Both the traditional and advanced capital goods sectors manufacture the associated capital goods. The following simplifying assumptions are made. First, the home country is a small 4 open economy; the foreign country (i.e., the rest of the world) is essentially a closed economy. All the foreign variables are denoted with the superscript *. The home economy is thus a price taker of the world’s final output and global interest rate. Second, both X and Y are tradable. The home country has relatively abundant less-skilled labor in the sense that L / H L* / H * with H H * , meaning that under free trade the home country has a comparative advantage in the traditional output. All other parameters are the same for both countries. Third, capital goods are not traded, labor does not move across the border, and international knowledge only spills over from the advanced R&D sector of the foreign country to its counterpart in the home economy. Finally, traditional goods X are treated as the numeraire. The production of final goods is specified as Z X ( LX )1 uj dj, 0 0 1, A Y ( HY )1 vj dj , (1) (1)' 0 where LX and HY are the associated labor inputs for producing X and Y , respectively; u j and v j are the employment of the j th type of capital goods for producing X and Y , respectively; and Z and A are the measures of the varieties of capital goods in the traditional and advanced sectors, respectively, with A specified to be larger than Z to ensure the positive skill premium. The evolutions of the measures of varieties for the home country are specified as follows: Z dZ A Z 1 LZ , dt A ( A* ) A1 H A , 0, 0 1, (2) 0, 0 1. (2)’ In equation (2), intra-national (sectoral) knowledge spillover is allowed in that technology spills over from the advanced R&D sector to the traditional R&D sector with 5 as the sectoral spillover efficiency and 0 1 . The IKS is allowed in equation (2)’ in that technology spills over from the advanced foreign R&D sector to the advanced home R&D sector with being the IKS efficiency and 0 1 .9 Note that and indicate the production efficiency of the two R&D sectors, respectively. The term LZ ( H A ) is the only paid input in the traditional (advanced) R&D sectors. Intra-national spillover from skill intensive industries and/or firms to their less skilled counterparts is evident.10 It is noted that ( A / Z ) in equation (2) captures the one-way positive sectoral spillover, and the effect increases with the skill discrepancy between the advanced and the traditional R&D sector, i.e., A / Z .11 Likewise ( A* / A) in equation (2)’ captures the IKS effect in the skilled home R&D sector. A* contributes to the evolution of A so as to echo both the theoretical and empirical findings that openness to trade enables the developing country’s products to embody foreign knowledge and to enhance productivity [Grossman and Helpman (1991), Ben-David and Loewy (2000), and Branstetter (2001)]. Despite missing a direct effect for the IKS on the traditional R&D sector, equations (2) and (2)’ together do imply that the evolution of Z is indirectly affected by A* . Assume that markets for final goods are competitive. The objective function of the Z Z 0 0 representative firm in sector X is X ( LX )1 uj dj P(u j )u j dj WLX LX , where P(u j ) is the rental price of the traditional capital good j ; and WLX is the wage rate of L X . Under a symmetric setup ( u j u ), the optimality conditions are 0 is the case with no IKS. See for example, Fang, Huang, and Wang (2008); Bernstein and Nadiri (1988); Griliches (1992), Branstetter (2001); and Keller (2002) for theoretical concerns and empirical support. 11 We can alternatively specify equation (2) to be Z [A (1 ) Z ]Lz . The results are, however, similar. It is also noted that the model reduces to the case with no sectoral spillover if 0 . 9 10 6 WLX (1 )( LX ) Zu and P(u ) ( LX )1 u 1 . (3) (4) Similarly, the optimality conditions for the representative firm in sector Y are WHY (1 ) PY ( HY ) Av and P(v) PY ( H Y )1 v 1 , (3)’ (4)’ where W H Y is the wage rate for H Y ; PY is the price of Y ; and P (v ) is the rental price of the advanced capital good. For simplicity, we assume that one unit of capital good is produced by one unit of the associated final good, and that the two capital goods markets are monopolistically competitive. The instantaneous profit functions for the capital goods producers are u P(u)u ru and v P(v)v rPY v, (5) (5)’ where r is the real interest rate. Using equations (4) and (4)’, the optimality conditions of the capital goods producers are 2 ( LX )1 u 1 r 2 ( H Y )1 v 1 r . and (6) (6)’ Substituting equations (4) and (6) into equation (5) and equations (4)’ and (6)’ into equation (5)’, respectively, we obtain u v 1 1 ru and rPY v . (7) (7)’ We assume in a competitive market that the R&D firm in each sector will sell its 7 blueprints to the capital goods producers at prices PZ and PA . With a constant r ,12 PZ and PA can be derived as follows: PZ e rt u (t )dt 0 PA 0 e rt v (t )dt 1 1 and u (8) PY v . (8)’ Due to free entry, these are the prices of the blueprints that make the monopolistically competitive firms with zero economic profit. As to the two R&D sectors, the representative firm’s profit functions are Z PZ Z WL LZ Z and A P A A WH H,A A where WLZ and WH A are the wage rate for LZ and H A , respectively. Using equations (2) and (2)’, the optimality conditions are WLZ PZ A Z 1 and WH A PA ( A ) A1 . (9) (9)’ Equation (9) says that the real wage paid by the R&D firm is equal to the marginal product of low skilled labor, which depends upon the sectoral spillover, i.e., ( A Z ) , and equation (9)’ says that the real wage received by the skilled labor depends upon the international spillover, i.e., ( A A) . The equilibrium in the two labor markets requires LX LZ L and HY H A H . (10) (10)’ Assume free mobility for each type of labor between the associated final goods sector and the R&D sector. Arbitrage then implies that 12 r is constant in a balanced growth equilibrium. 8 WLX WLZ WL and (11) WHY WH A WH . (11)’ Using equations (3), (9), (3)’ and (9)’, equations (11) and (11)’ give rise to 1 Z PZ ( LX ) u A PA 1 PY ( H Y ) v ( and A ) . A (12) (12)’ These are blueprint prices that allow R&D firms to employ labor to engage in their R&D activities. Labor arbitraging between the final goods sector and the R&D sector results in a PZ that rises with (Z / A) . The logic is as follows. The higher the skill discrepancy ( A Z ) is, the higher the productivity of the traditional R&D sector that can be obtained through sectoral spillover. Other things being equal, this causes the supply of less-skilled blueprints to increase and thus lowers PZ . The same reasoning applies to the result that PA rises with ( A A ) . Equating PZ from equations (8) and (12) and PA from equations (8)’ and (12)’ implies that u 1 A ( ) ( LX ) Z v 1 A* ( ) ( HY ) . A and (13) (13)’ These two equations demonstrate the relationship between the employment of capital goods and labor in the two final goods sectors. When the skill discrepancy is larger, unskilled labor benefits more from the sectoral spillover and thus less capital goods are needed to produce the same amount of traditional final goods. The demand side of the economy is specified below. The optimization problem 9 facing the representative household in the economy is max t 0 e [ log CX (t ) (1 ) log CY (t )] dt , s.t. rt rt 0 e [CX (t ) PY (t )CY (t )] dt 0 e [WL (t ) L WH (t ) H ]dt , where is the time preference rate; and C X and CY are the consumption of the two final goods, respectively.13 Let g be the growth rate along a balanced growth path (hereafter BGP), i.e., C Z A C X Y g X Y . Given the optimality conditions from the above Z A C X CY X Y maximization problem, we obtain the following results, under the assumption that the home country is a small both in the international goods market and the capital market: (1 )C X CY PY PY and (14) g r r . (15) Moreover, the aggregate resources constraints in the economy are X CX Z u and (16) Y CY Av . (16)' g * and PY* , along the BGP, can be obtained for the foreign country by g* r* H * 1 1 1 1 L* P H * * Y and 14 (17) 1 . (18) We now make some remarks on the above results. First, the main features of Romer 13 The intertemporal budget constraint is equivalent to the asset’s law of motion with a transversality condition imposed. 14 A mathematical appendix explaining the derivation of the equations in this paper is available upon request. 10 type models are preserved in equation (17), specifically, the perpetual growth increases with the amount of skilled labor and the efficiency at the skilled R&D sector in the economy. Second, equation (18) indicates that the relative price of the advanced final goods PY* , is determined by the relative supply of skilled labor as well as the spillover efficiency. A higher relative endowment H L induces a larger relative supply of the advanced goods and thus a lower relative price. On the other hand, a higher efficiency of sectoral spillover, i.e., a larger , implies a higher productivity of R&D labor in the traditional sector, thus enlarging the variety of capital goods in the traditional final goods sector. It in turn increases the supply of traditional final goods X and therefore causes the price to fall and the relative price PY to rise. Finally, PY* is the world price faced by the home country, and the growth rate of the foreign country g * is also the growth rate of the home country along the BGP under free trade, for g r r g .15 The analytical solutions of H A , H Y , LX , LZ , v , u , A/ Z , etc., for the home country can now be easily obtained once the growth rate g is known. Take for example, Z A r g g Z ( ) LZ Z Z and (19) A A* r g g A ( ) H A . A A (19)’ Therefore, via equations (19) and (13) and equations (19)’ and (13)’, respectively, we obtain g 15 ( A / Z ) L 1 Since the foreign country is essentially a closed economy, and (20) r * is determined in exactly the same way as * r is determined in an autarky economy. To be specific, r * ( H ) . 1 11 g ( A* / A) H . 1 (20)’ Under free trade, g g . Combining this with equations (20) and (19) gives rise to the following skill discrepancy for the home country: 1 H * 1 (1 )( ) * H A (1 ) g 1 . Z L L L 1 (21) Equation (21) shows that the domestic skill discrepancy between the two R&D sectors depends upon the relative size of the foreign skilled labor endowment, as opposed to the domestic skilled labor, to the domestic unskilled labor along the BGP. It is essentially due to the fact that the international knowledge spills over directly from A* to A and indirectly from A to Z along the BGP. Therefore, through the effects of A* on A , the domestic skill discrepancy A / Z is determined by ( H * / L) . Equation (21) can be rewritten as 1 1 A H * H * H ( )( ) . Z L H L (22) Holding ( / ) constant, it is evident that determination of the domestic skill discrepancy between the two R&D sectors comprises two forces: the relative size of the skilled labor in the foreign country compared to its counterpart in the home country, and the relative supply of skilled labor in the home country. The larger either of the above two terms, the larger the domestic skill discrepancy. To be more specific, the skill discrepancy is affected positively by the relative supply of skilled labor in the foreign and the home country, and the relative supply of domestic skilled and unskilled labor. Furthermore, the skill discrepancy varies inversely with the sectoral spillover efficiency from the advanced R&D sector to the traditional R&D sector. 12 Similarly, the equilibrium skill discrepancy between the home country and the rest of the world, as derived from equations (17) and (20)’, is determined by the relative supply of skilled labor as follows: 1 A* (1 ) g A H 1 H * 1 (1 )( ) * H 1 . H H (23) Note that, according to equation (19)’, other things being equal, an increase in the IKS efficiency can cause A to increase at any point of time along the BGP. That is to say, a change in has a level effect for the home country although it does not show a growth effect for g * r * ( H * ) /(1 ) . Similarly, other things equal, a change in H has a level effect, but no growth effect. 3. A Comparison of the Wage Premium under Autarky and International Trade With a view to examining the effect of trade on wage inequality in developing countries, we now let superscripts tr and au denote variables pertaining to the home country under free trade and under autarky, respectively. The wage inequality between skilled and less-skilled labor can be obtained for the home country under free trade as follows: tr WH PY* ( HY ) Av A PY* = ( LX ) Zu Z WL tr 1 1 1 * 1 * 1 L H . H * L (24) 13 Several points should be highlighted. First, the second equality in equation (24) indicates that the wage inequality under free trade hinges on the relative price and the skill discrepancy; the magnitudes of the two forces are shown in the last equality of equation (24). Second, the last equality of equation (24) implies that the larger the sectoral knowledge spillover across various skilled workers, the smaller the wage premium for skills is. Finally, from equation (24), it is also evident that a change in will not affect (WH / WL ) , for the world price PY* is not influenced by , and A and Z change proportionally along the BGP. It is worth mentioning that in the study by Acemoglu (2002) the factors that determine the wage premium are the price effect and the market size effect. In relation to the price effect, he reaches the conclusion that the wage premium in northern countries rises in response to an increase in the relative supply of skilled labor. In equation (24) of our model however, it is shown that a change in the relative supply of skilled labor in a small developing (home) country (with both international and sectoral knowledge spillovers) does not give rise to an increase in wage inequality. We now compare wage premiums under free trade with that under autarky. tr W W A A ( H )tr ( H )au PY* PYau WL WL Z Z 1 1 1 1 L* * H 1 1 au 1 * H 1 L 1 1 L H 1 1 H L 1 H * 1 H * H [( * ) ( ) ( ) -1 ] . L L L (25) Observe from the second equality in equation (25) that PYtr PY* PYau and A Z au A Z . tr This is due, on the one hand, to the assumptions that unskilled labor is relatively 14 abundant in the home country and that the two countries have the same preferences. A fall in the price of the advanced goods after trade causes the wage inequality of home country to fall. This is the so-called price effect. On the other hand, the domestic skilled sector directly benefits from international knowledge spillovers; the domestic unskilled sector is affected only indirectly. Consequently, skill discrepancy in the two sectors, as measured by the ratio A / Z , will increase as we move from autarky to free trade, and therefore the wage inequality of the home country rises. This is the skill discrepancy effect. One may argue that IKS affects not only the skilled R&D sector, but also the less-skilled R&D sector in the home country, and the skill discrepancy effect in equation (25) would be loosened. Nonetheless, compared to skilled labor, less-skilled labor is less efficient at absorbing international knowledge, and the skill discrepancy effect shall not be fully offset. As a consequence, wage inequality in a small open developing country is thus driven by two opposing forces: a fall in the relative price of the advanced goods that reduces wage inequality and a rise in skill discrepancy that increases wage inequality. The former confirms the Stolper-Samuelson mechanism, whereas the latter force contradicts the effect of the Stolper-Samuelson mechanism. Our proposed model can thus explain diverse wage inequality movements observed in the empirical evidence after developing countries have been opened up to international trade. The declining of wage inequalities in Taiwan and South Korea after increased openness to trade in the 1960s and the widening of wage inequalities that occurred in some Latin American countries in the 1980s provide excellent examples on which to apply our model. It is well documented that the U.S. and many OECD countries have experienced fundamental changes in the pattern of wage inequality between skilled and unskilled labor in the last three decades. Specifically, a decline has been documented as in the US from the late 1960s to the mid 1970s, and then a sharp increase in the 1980s 15 and 1990s [Juhn, Murphy, and Pierce 1993; Autor, Katz, and Krueger 1998; Goldin and Katz 1998; and Juhn 1999]. In many OECD countries, such as Finland and Sweden, it has been demonstrated that earnings inequality increased during the 1980s following a sharp decline during the 1970s [Gottschalk and Smeeding 1997]. Speedy (slower) technological change has been recognized as one of the main driving forces behind the increasing (decreasing) inequality in already developed countries. It is thus plausible that the IKS effect was much stronger and more influential in the 1980s than in the 1960s. Evidence shows that decreases in the wage inequalities in developed countries in the 1960s coexisted with decreasing wage inequality in Taiwan and South Korea. It can be reasoned that since IKS was weaker, due to slower technological change in the developed countries during that time period, so was the skill discrepancy effect. On the other hand, the increasing wage inequalities in most developed countries in the 1980s and 1990s, due to faster technological change, coexisted with the widening of wage inequalities in Latin American countries who became involved in free trade with more developed partners in the 1980s [Zhu and Trefler 2005; Freeman and Oostendorp 2001]. The case of Taiwan and South Korea in the 1960s illustrates a situation where the price effect was dominant after the opening of trade, while the Latin American case in the 1980s is a result of the dominance of the skill discrepancy effect. Our model thus supports the results reported in the literature, offering a sensible and plausible explanation for empirical evidence of diverse movements in terms of wage inequalities in developing countries that have been opened to trade. 4. Conclusion Empirical evidence indicates that the Stolper-Samuelson mechanism seems to ignore factors that force wage inequalities to increase, leading to an uncertain outcome when developing countries are opened to trade. The main purpose of this study is thus to 16 propose a theoretical framework that is capable of predicting the above uncertainties. To be more specific, we set up a two country trade model between a (large) developed and (small) developing country that takes into account international and intra-national knowledge spillovers, and examine the effects of openness to trade on wage inequality. In our model there are essentially two opposite effects which determine wage inequality in a small a small developing country after it has been opened up to trade, the price effect and the skill discrepancy effect. The former reduces wage inequalities and the latter increases wage inequalities. It is these two competing forces that have led to the uncertainty in prediction of the effects of trade openness on wage inequality in small developing countries. We outline a model that can explain the empirical evidence, the inconsistent movements in wage inequality in different countries. It thus complements the literature in explaining the southern wage inequality. Acknowledgements We are grateful for the helpful comments made by seminar participants at National Central University, Tamkang University, and National Taipei University. Financial support was provided by the National Science Council of Taiwan under grant NSC 92-2415-H-008-003 to M. Wang. 17 References: Acemoglu, D., 2002, “Directed Technical Change”, Review of Economic Studies, 69, 781-809. Aghion, P., 2002, “Schumpeterian Growth Theory and the Dynamics of Income Inequality,” Econometrica, 70, 855-882. Aghion, P., E. Caroli, and C. Garcia-Penalosa, 1999, “Inequality and Economic Growth: The Perspective of the New Growth Theories,” Journal of Economic Literature, 37, 1615-60. Autor, D. H., L. F. Katz and A.B. Krueger, 1998, “Computing Inequality: Have Computers Changed the Labor Market?” Quarterly Journal of Economics, 113, 1169-1213. Beaulieu, E., M. Benarroch and J. Gaisford, 2004, “Trade Barriers and Wage Inequality in a North-South Model with Technology-Driven Intra-Industry Trade,” Journal of Development Economics, 75, 113-136. Ben-David, D. and M. B. Loewy, 2000, “Knowledge Dissemination, Capital Accumulation, Trade, and Endogenous Growth,” Oxford Economic Papers, 52, 637-650. Bernstain, J. and P. Mohnen, 1998, “International R&D Spillovers between U.S. and Japanese R&D Intensive Sectors,” Journal of International Economics, 44, 315-38. Bernstein, J. and M. I. Nadiri, 1988, “Interindustry R&D Spillovers, Rates of Return, and Production in High-Tech Industries,” AEA Papers and Proceedings, 78, 429-434. Branstetter, L. G., 2001, “Are Knowledge Spillovers International or Intranational in Scope? Microeconometric Evidence from the U.S. and Japan,” Journal of International Economics, 53, 53-79. Coe, D. T. and E. Helpman, 1995, “International R&D Spillovers”, European Economic 18 Review, 39, 859-887. Coe, D. T., E. Helpman and A. W. Hoffmaister, 1997, “North-South R&D Spillovers”, Economic Journal, 107, 134-149. Chuang, Y., 1997, “Knowledge Spillover, Trade and Economic Growth”, Journal of International and Comparative Economics, 5, 249-269. Deardorff, A. V., 1994, “Overview of the Stolper-Samuelson Theorem”, in Deardorff A. V. and R. M. Stern (eds.), The Stolper-Samuelson Theorem: A Golden Jubilee. Ann Arbor: University of Michigan Press. Engelbrecht, H., 2002, ”Human Capital and International Knowledge Spillovers in TFP Growth of a Sample of Developing Countries : An Exploration of Alternative Approaches ,” Applied Economics, 34, 831-41. Fang, C. R., L. H. Huang and M. C. Wang, 2008, “Technology Spillover and Wage Inequality “, Economic Modelling, 25(1), 137-147. Feenstra, R. and G. H. Hanson, 1996, “Globalization, Outsourcing, and Wage Inequality,” American Economic Review, 86, 240-245. Fischer, R. D., 2001, “The Evolution of Inequality after Trade Liberalization,” Journal of Development Economics, 66, 555-579. Freeman, R. B. and R. H. Oostendorp, 2001, “The Occupational Wages around the World Data File,” International Labor Review, 140, 379-401. Galor, D. and D. Moav, 2000, “Ability-biased Technological Transition, Wage Inequality, and Economic Growth,” Quarterly Journal of Economics, 115, 469-97. Glazer, A. and P. Ranjan, 2003, “Preference Heterogeneity, Wage Inequality, and Trade,” Journal of International Economics, 60, 455-469. Goldin, C. and L. F. Katz, 1998, “The Origins of Technology-skill Complementarity,” Quarterly Journal of Economics, 113, 693-732. 19 Gottschalk, P. and T. M Smeeding, 1997, “Cross-national Comparisons of Earnings and Income Inequality,” Journal of Economic Literature, 35, 633-687. Griliches, Z., 1992, “The Search of R&D Spillovers,” Scandinavian Journal of Economics, 94, S29-47. Grossman, G. M. and E. Helpman, 1991, “Trade, Knowledge Spillovers, and Growth,” European Economic Review, 35, 517-526. Juhn, C., 1999, “Wage Inequality and Demand for Skill: Evidence from Five Decades,” Industrial and Labor Relations Review, 52, 424-443. Juhn, C., K. M. Murphy and B. Pierce, 1993, “Wage Inequality and the Rise in Returns to Skill,” Journal of Political Economy, 101, 410-442. Keller, W., 2002, “Trade and Transmission of Technology,” Journal of Economic Growth, 6, 5-24. Lichtenberg, F. R. and B. P. Potterie, 1998, “International R&D Spillovers: A Comment,” European Economic Review, 42, 1483-1491. Lloyd-Ellis, H., 1999. "Endogenous Technological Change and Wage Inequality,” American Economic Review, 89, 47-77. Long, N. V., R. G. Riezman and A. Soubeyran, 2004, “Trade, Wage Gaps and Specific Capital Accumulation,” forthcoming in the Review of International Economics. Marjit, S., H. Beladi and A. Chakrabarti, 2004, “Trade and Wage Inequality in Developing Countries,” Economic Inquiry, 42, 295-303. Murat, M. and F. Pigliaru, 1998, “International Trade and Uneven Growth: a Model with Intersectoral Spillovers of Knowledge,” The Journal of International Trade and Economic Development, 7, 221-236. Robbins, D. J., 1996, “HOS Hits Facts: Facts Win; Evidence on Trade and Wages in the Developing World, mimeo, Harvard Institute for International Development. 20 Ripoll, M., 2005, “Trade Liberalization and the Skill Premium in Developing Countries,” Journal of Monetary Economics, 52, 601-619. Romer, P. M., 1990, “Endogenous Technological Change,” Journal of Political Economy, 98, S71-S102. Stokey, N. L., 1996, “Free Trade, Factor Returns, and Factor Accumulation,” Journal of Economic Growth, 1, 421-447. Wood, A., 1996, “Openness and Wage Inequality in Developing Countries: the Latin American Challenge to East Asian Conventional Wisdom,” in R. E. Baldwin, D. Cohen, A. Sapir and A. Venables (eds.), Market Integration, Regionalism and the Global Economy, Center for Economic Policy Research, Cambridge University. Xu, B., 2003, “Trade Liberalization, Wage Inequality, and Endogenously Determined Nontraded Goods,” Journal of International Economics, 60, 417-431. Zhu, S. C., 2004, “Trade, Product Cycles and Inequality Within and Between Countries,” Canadian Journal of Economics, 37, 1042-1060. Zhu, S. C. and D. Trefler, 2005, “Trade and Inequality in Developing Countries: A General Equilibrium Analysis,” Journal of International Economics, 65, 21-48. 21