“Reducing barriers to trade is not enough to fulfill the development promise of Doha. Trade must be part of a larger development strategy for each country, a strategy that includes attention to macroeconomic policy, infrastructure, education, and health as well as to accountable and responsible governance. These elements of investment climate take time to develop but are essential for growth and poverty reduction and are crucial to make a sound strategy pay its growth and poverty reduction dividends.”—Nicholas Stern, Chief Economist and Senior Vice President, World Bank, “Global Economic Prospects—Realizing the Development Promise of Doha Agenda: 2004.”
Amiti, M., and S-J Wei (October 2004). “Fear of Service Outsourcing: Is it Justified?” IMF Working Paper, Research Department, WP/04/186. pp. 1-42.
Anand, Sudhir and Amartya Sen (1997). “Concepts of Human Development and Poverty: A Multidimensional Perspective.” In Poverty and Human Development, Human Development Papers. Human Development Report Office. The United Nations Development Programme, NY, USA.
- Search Google Scholar
- Export Citation
)| false ( Anand, Sudhirand Amartya Sen 1997). “ Concepts of Human Development and Poverty: A Multidimensional Perspective.” In Poverty and Human Development, Human Development Papers. Human Development Report Office. The United Nations Development Programme, NY, USA.
Autor, David . (November, 2001). “Why do Temporary Help Firms Provide Free General Skills Training?” Quarterly Journal of Economics.
Autor, David . (2002). “Outsourcing at Will: Unjust Dismissal Doctrine and the Growth of Temporary Help Employment.” Journal of Labor Economics.
Barro, R. J. and J. W. Lee (1996). “International Measures of Schooling Years and Schooling Quality.” Papers and Proceedings of American Economic Review. 86 (2), pp. 218-223.
Bartel, A., S. Lach, and N. Sicherman (February 2005). “Outsourcing and Technological Change.” Working Paper # 1158, NBER, pp. 1-37.
Berg, A., and A. Krueger (2003). “Trade, Growth, and Poverty—A Selective Survey,” Annual World Bank Conference on Development Economics 2003, World Bank.
Bhagwati, J. (1993), Regionalism and Multilateralism: An Overview, J. de Melo and A. Panagariya (eds), New Dimensions in Regional Integration (NY: Cambridge University Press).
Bleaney, Michael and Akira Nishiyama (2004). “Some international evidence on Poverty Alleviation and Economic Growth.” The European Journal of Development Research. 16 (4), pp. 827-844.
Bourguignon, Francois (March 2004). “The Poverty-Growth-Inequality Triangle.” Working Paper No. 125, Indian council for Research on International Economic Relations, New Delhi, India.
Bourguignon, Francois (2003). “The Growth Elasticity of Poverty Reduction: Explaining Heterogeneity across Countries and Time Periods.” In T. Eicher and S. Turnovsky, eds. Inequality and Growth: Theory and Policy Implications. Cambridge: MIT Press.
Bussolo, Maurizio and David O’Connor (2002). “Technology and Poverty: Mapping the Connections.” In Jorge Braga de Macedo and Tadao Chino (eds.), Technology and Poverty Reduction in Asia and the Pacific. Development Centre Seminars, OECD.
Cline, W. R. (2004). “Trade Policy and Global Poverty.” Centre for Global Development, Institute for International Economics. Washington DC, USA.
Chen, S., and M. Ravallion. (2004). “How Have the World’s Poorest Fared since the Early 1980s?” The World Bank Research Observer, 19 (2), World Bank, pp. 141-169.
Cohen, W. M., and D. A. Levinthal (1989). Innovation and Learning: The Two Faces of R&D. The Economic Journal 99 (September): 569-596.
Cohen, W. M., and D. A. Levinthal (1990). Absorptive Capacity: A New Perspective on Learning and Innovation. Administrative Science Quarterly 35 (1): 128-52.
Das, Gouranga G. (2002). “Trade, Technology and Human Capital: Stylised Facts and Quantitative Evidence”-The World Economy, Volume 25, Issue 2, Blackwell Publishers, Oxford (U.K.) & Boston (U.S.A.).
De Ferranti, D., G. E. Perry, I. S. Gill, J. L. Guasch, W. F. Maloney, C. S. Paramo, and N. Schady (2003b). Closing the Gap in Education and Technology. The World Bank, Washington.
De Janvry, A., G. Graff, E. Sadoulet and D. Zilberman (2000), “Technological change in Agriculture and Poverty Reduction,” A Concept Paper for the World Development Report on Poverty And Development, 2000/01, World Bank, Washington DC, processed.
De Rosa, D. A. (1998). “Regional Integration Arrangements: Static Economic Theory, Quantitative Findings, and Policy Guidelines”, background paper for a World Bank Policy Research Report, Regionalism and Development,Virginia: ADR International Ltd.
Deininger, K., and L. Squire (1996). “A New Dataset measuring Income Inequality,” The World Bank Economic Review 10 (3), pp. 565-591.
Dimaranan, B., R. A. A. Mc Dougall (eds.) (2003). Global Trade, Assistance, and Protection: The GTAP 5 Database, Center for Global Trade Analysis, Purdue University, USA.
Dyke, Nancy Berg (2001) in Aspen Institute Conference Report on International Peace, Security and Prosperity (2001), “Attacking Global Poverty: Technology for Economic and Social Uplift.” August 18-20, 2000, Aspen, Colorado.
Eaton, J. and S. Kortum (1996). Trade in Ideas: Patenting and Productivity in the OECD. Journal of International Economics 40: 251-278.
Francois, J. F. and C. R. Shiells (1994), “AGE Models of North American Free Trade’ in J. F. Francois and C. R. Shiells , (eds) Modeling Trade Policy, Applied General Equilibrium Assessments of North American Free Trade, (Cambridge: Cambridge University Press).
- Search Google Scholar
- Export Citation
)| false ( Francois, J. F.and C. R. Shiells 1994), “ AGE Models of North American Free Trade’ in , ( J. F. Francoisand C. R. Shiells eds) Modeling Trade Policy, Applied General Equilibrium Assessments of North American Free Trade, ( Cambridge: Cambridge University Press).
Groot, H. L. F. de., G-J Linders, P. Rietvelda, and U. Subramanian (2004). The Institutional Determinants of Bilateral Trade Patterns. Kyklos 57 (February):103-124.
Gunter, B. G., M. J. Cohen, and H. Lofgren (2005). “Analysing Macro-poverty Linkages: An Overview.” Development Policy Review, 23 (3), pp. 243-265.
Harrison, W. J. and K. R. Pearson (1996) “Computing Solutions for Large General Equilibrium Models Using GEMPACK.” Computational Economics, 9: pp. 83-127.
Hertel, T. W., and J. J. Reimer (November 2004). “Predicting the Poverty Impact of Trade Reform.” World Bank Policy Research Working Paper 3444, World Bank.
Huang, J. and S. Rozelle (1996), “Technological Change: Rediscovering the Engine of Productivity Growth in China’s Rural Economy.” Journal of Development Economics, 49.
Huang, J., R. Hu, H. van Meijl, and F. van Tongeren (2004). “Biotechnology boosts to crop productivity in China: trade and welfare implications.” Journal of development Economics, 75, pp. 27-54.
Kaufmann, D. A. Kraay, and M. Mastruzzi (2003). Governance Matters III: Governance Indicators for 1996–2002. World Bank Policy Research Working Paper 3106. Dataset at:www.worldbank.org/wbi/governance/govdata2002/.
Kaufmann, D (2004). Governance Redux: The Empirical Challenge. Chapter in Global Competitiveness Report 2003-2004, World Economic Forum.
Keller, W. (2001). The Geography and Channels of Diffusion at the World’s Technology Frontier. NBER Working Paper, 8150, Cambridge, MA, 1-28 + Appendix.
Milanovic, B., and L. Squire (January 2005). “Does Tariff Liberalization Increase Wage Inequality? Some Empirical Evidence.” NBER Working Paper 11046, Massachusetts, Cambridge, USA. Pp. 1-65.
McCulloch, N., L. Alan Winters, and X. Cirera (2001). “Trade Liberalization and Poverty: A Handbook.” CEPR and Department for International Development., U.K.
McDougall, R. (October 2003). Release Notes for GTAP.Tab 6.2. GTAP Center, Purdue University, USA.
Meijl, H. van, and F. W. van Tongeren (1998). Trade, Technology Spillovers, and Food Production in China. Weltwirtschaftliches Archiv 134 (3):443-449.
Nelson, R.R. (1990). On Technological Capabilities and their Acquisition. In R.E. Evenson and G. Ranis (eds.), Science and Technology: Lessons for Development Policy, Westview Press.
Pack, H., and L. E. Westphal (1986). “Industrial Strategy and Technological Change: Theory versus Reality.” Journal of Development Economics, 87, pp. 87-128.
Ravallion, M. (2004). “Looking Beyond Averages in the Trade and Poverty Debate.” World Bank Policy Research Working Paper 3461. Washington D.C.: World Bank.
Richardson, J. D. (1995). “Income Inequality and Trade: How to Think, what to Conclude.” Journal of Economic Perspectives, 9, pp. 33-55.
Robinson, S., and H. Lofgren (2005). “Macro Models and Poverty Analysis: Theoretical Tensions and Empirical Practice. Development Policy Review, 23 (3), pp. 267-283.
Sen, A. (1993). “Capability and Well-being”, in The Quality of Life, (eds.) Martha Nussbaum and A. Sen. Oxford: Clarendon Press.
Winters, A. L., N. McCulloch, and A. McKay (March 2004). “Trade Liberalization and Poverty: The Evidence So Far.” Journal of Economic Literature, Volume XLII, Number 1, pp. 72—115.
World Bank (2004b). Global Economic Prospects 2004: Realizing the Development Promise of the Doha Agenda. Washington D.C.: World Bank.
UNDP. Human Development Report 2003: Millenium Development Goals: A Compact among Nations to end Human Poverty. New York, Oxford University Press.
Department of Economics, Hanyang University, South Korea. The initiation stage of writing this paper was during the author’s short stint at the IMF, in Washington, DC, during winter 2005. Acknowledgements are due to the Global Development Network and the IMF for financial support under the IMF-GDN Network’s fifth Visiting Scholars Program. The hospitality of the IMF is gratefully appreciated. Also, the academic support of Andrew Feltenstein at the IMF needs special mention. Special thanks go to Alan Powell. However, usual caveat applies.
During the past few years and at present, debates on the effect of trade on wage inequality have continued. Especially, it has been argued that skill vis-à-vis unskilled wage inequality has been caused by a concomitant rise in trade under the onslaught of globalization. Thus, globalization is a cause behind wage inequality (Wood 1994, Bhagwati and Kosters 1994; Marjit and Acharya 2003; and Milanovic and Squire 2005). However, trade and wage inequality linkages are not explored here.
Version 6 or beta release of the GTAP database incorporates more regional split whereas number of sectors remain the same. During the time of conducting research, this was not available. However, this does not undermine our purpose because those regions are not subject of study in this paper—rather; those are clustered into composite rest-of-the-world region.
Alternatively, for computing the Ginis, for Ppoor we have also taken percentage of people below national poverty line and 50% of median income for developed nations as proxy of proportion of people below poverty line and hence, poor. This measure is not accurate because we do not know Prich and that creates computational problem. However, because the GTAP database has skilled income payment share we adopt tertiary education enrolment level as proxy of skill population. Considering data on percentage of population below poverty line of bottom, we derived the measure of income inequality across income groups. But, we do not report those for parsimony. However, this does not undermine our purpose because GTAP’s skill decomposition is based on educational attainment data as described in Barro-Lee (1996).
An alternative specification using a linear relationship under OLS shows the same causality and direction. The value of R2 = 0.82.
Chapter 2: The Debate over Trade Liberalization. Trade Liberalization and Poverty: A Handbook, CEPR.
IT products include SITC (revision 2 and 3) classification categories 75, 76 and 776. These are automatic data processing instruments such as computers, calculators, photocopy machines, etc. and also, electronic components including semiconductors, electronic tubes and valves, telecommunications and radio equipment. However, these are not exhaustive but ‘representative’ classification in the absence of detailed classification and dearth of data.
According to the OECD (1997), technology is broadly defined as direct and indirect R&D embodiment of various types of intermediate inputs and capital goods.
Average annual growth rates are calculated using Ordinary Least Square (OLS) method.
According to Human Development Report (p. 47, 2001), Technological Achievement is important for human development and the Index correlates with the Human Development Index.
For example, in case of India, there is technological hub like Bangalore, the centre of outsourcing activities and software technology development, but this is not spread in other regions in India uniformly because of low adult literacy rate, low tertiary enrolment rate and uneven diffusion of technology across regions within India. Thus, although a state like Bangalore has high achievement index the overall index for India is low in value.
Thus, international trade in commodities facilitates propagation of superior ‘technologies’ embodied in those traded goods and services (Dietzenbacher 2001; Eaton and Kortum 1996; Keller 2001, 2004; World Development Report, The World Bank, 1999 for empirical evidences). The nexus between relative income level and the growth rate of the trading partners has been discussed at length (for example, Schiff and Wang, 2004). Role of FDI in technology transfer is also emphasized in the literature. However, the primary emphasis being on the trade flows in the medium-run, we focus solely on trade as a vehicle of advanced technology.
Keep in mind that here “macro” means common across all sectors and intermediate inputs in the client region.
One could consider Gini distribution of inequality in labor productivity. However, here we consider effect of productivity spillover on income inequality and hence, such issue is not considered.
Human Poverty Index is an alternate measure of income poverty and it is deprivational index (see Anand and Sen 1997). It includes three components viz., survival deprivation, educational and knowledge deprivation, and economic deprivation.
One could have an inverse linear specification where Gconvert = 1- F(Ginitial, θ). However, this is not strong specification. Alternatively, another nonlinear specification is Cobb-Douglas:
Chen and Ravallion (2004, World Bank Research Observer) defines Poverty Gap, PG = [1 – ratio of mean income of the poor to the poverty line] × Head count ratio.
GTAP 6 is the latest release of the database based solely on the beta release of Version 5.4 database. However, Version 6 extends the beta release to more regions with same number of sectors and those regions are not subject of analysis in the present research and hence, it does not undermine our purpose.
These indicators for perceived institutional quality are: Voice and accountability, Political stability, Government effectiveness, Regulatory quality, Rule of law, and Control of corruption. Although basic calculations and data sources are presented, the values of such parameters for AC, SA, TC and GP are not reported here for want of space.
By calculating the composite values of GP indices from its estimates of score of each of the 6 components, we get figures for Bangladesh and Sri Lanka as more negative compared to that in India. This implies better governance in India compared to those South Asian nations. But, taking absolute magnitude gives erroneous perceptions about this parameter. To avoid this inconsistency, we make adjustments by calculating regional averages of 6 indices (6.49) and then, take the difference of each of the countries GP values to compute the relative difference/distance from regional average of South Asia. This gives consistent measure of GP values of South Asian nations.
The reason behind choosing East and South East Asia as borderline case of threshold level is that these regions, over last two decades have embarked on a path of human resource–led development path and achieved remarkably high growth cycles. This miraculous performance sets them as a reference region (see East Asian Miracle, World Bank 1993).
This is developed by Ken R. Pearson and colleagues at the Centre of Policy Studies/IMPACT, Monash University, Australia based on GEMPACK software suite. See Harrison and Pearson (1996) for GEMPACK simulation software.
According to Keller (1999, 2001) the rate of growth of R&D stock in USA is 7.4% of which 90% is originating in manufacturing comprising hi-tech and heavy manufacturing. That is, the growth of R&D in manufactures especially in two sectors heavy manufacturing and hi-tech. is 0.90×7.4%= 6.4% (approximately). Simple average of the TFP indexes in these 2 sectors is also 3.2%
Due to limitations of space, we report only selected most important ones.
In terms of the actual policy experiment, we assume that each arrangement consists of an immediate (i.e., no phasing-in), complete (i.e., no excluded sectors and no partial liberalization) and preferential (i.e., no liberalization with non-members) removal of the relevant tariffs and any quantifiable non-tariff barriers.
In particular, using the updated database from the previous experiment, we simulate trade liberalization between the spokes—India and China—to have full-fledged liberalization among the three players.
On the contrary, in a reverse sequence where at first China forms FTA with USA and then with India, the technological benefits will be harnessed by China at later stage only when USA liberalizes trade with her. Blyde (2004) shows empirical supports for such direct and indirect trade-related technology flows.