This paper examines sources of economic growth in East Asia. The conventional growth-accounting approach to estimating the sources of economic growth requires unrealistically strong assumptions about either competitiveness of factor markets or the form of the underlying aggregate production function. The paper outlines a new approach utilizing nonparametric derivative estimation techniques that does not require imposing these restrictive assumptions. The results for East Asian countries show that output elasticities of capital and labor tend to be different from the income shares of these factors. The paper also explores the compensating potential of private intergenerational transfers.

China’s growth performance since the start of economic reforms in 1978 has been impressive, but the gains have not been distributed equally across provinces. We use a nonparametric approach to analyze the variation in labor productivity growth across China’s provinces. This approach imposes less structure on the data than the standard growth accounting framework and allows for a breakdown of labor productivity into efficiency gains, technological progress, and capital deepening. We have the following results. First, we find that on average capital deepening accounts for about 75 percent of total labor productivity growth, while efficiency and technological improvements account for about 7 and 18 percent, respectively. Second, technical change is not neutral. Third, whereas improvement in efficiency contributes to convergence in labor productivity between provinces, technical change contributes to productivity disparity across provinces. Finally, we find that foreign direct investment has a positive and significant effect on efficiency growth and technical progress.

Forty years ago, Marcus Fleming and Robert Mundell developed independent models of macroeconomic policy in open economies. Why do we link the two, and why do we call the result the Mundell-Fleming, rather than Fieming-Mundell model?

This second issue for 2004 contains 8 new papers, including notable contributions from: Nancy Brune, Geoffrey Garrett, and Bruce Kogut on the global spread of privatization; and Mark P. Taylor and Elena T. Branson on asymmetric arbitrage and default premiums in the U.S. and Russian markets. Other papers in the issue look at German wage structures, contagion in equity markets, export orientation and productivity in Sub-Saharan Africa, the role of higher vs. basic education in economic development, and issues related to capital account liberalization.

This paper examines contractionary currency crashes in developing countries. It explores the causes of India’s productivity surge around 1980, more than a decade before serious economic reforms were initiated. The paper finds evidence that the trigger may have been an attitudinal shift by the government in the early 1980s that, unlike the reforms of the 1990s, was pro-business rather than pro-market in character, favoring the interests of existing businesses rather than new entrants or consumers. A relatively small shift elicited a large productivity response, because India was far away from its income possibility frontier.

This paper analyzes the link between product variety and economic growth. It finds support for the hypothesis that a greater degree of product variety relative to the United States helps to explain relative per capita GDP levels. The paper presents an empirical study for South Africa, which indicates that there exists a stable money demand type of relationship among domestic prices, broad money, real income, and interest rates, as well as a long-term relationship among domestic prices, foreign prices, and the nominal exchange rate.

Noteworthy among the six papers appearing in this latest issue of the IMF's peer-reviewed journal is another installment in the Special Data Section. Anthony Pellechio and John Cady from the IMF's Statistics Department take a close look at differences in IMF data; how and when they could occur; and what the implications of such differences might be for end-users of the IMF's data.