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GTAP Resource #1755 |
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"The convergence hypothesis in the context of multi-country computable general equilibrium modelling" by Dixon, Peter and Maureen Rimmer Abstract Objectives: Convergence is often interpreted as meaning that GNP per capita in developing countries catches up to GNP per capita in developed countries. The aim of this paper is to show how convergence between developing and developed countries can be analysed in a computable general equilibrium (CGE) model. Our motivation is provided by the Castles/Henderson critique (2003 a & b) of the Special Report on Emissions Scenarios (SRES) by the Intergovernmental Panel on Climate Change (IPCC, 2000). The SRES is concerned with the greenhouse-gas implications of convergence. Castles and Henderson argue that the SRES may have overestimated the increase in greenhouse gases associated with convergence by using inappropriate measures of current per capita GNP for developing countries. Estimates of GNP per capita are readily available for most countries of the world in national currencies. When these estimates are converted by market exchange rates (MERs) into a common currency, they imply very large differences between developing and developed countries. For example, IMF statistics show that the $US value of GNP per capita in China at the MER was about $US800 in 2000. This is only about one fortieth of GNP per capita in the U.S. in 2000 (see IMF International Financial Statistics, China and U.S. pages, December 2000). Figures such as these give the impression that convergence will mean enormous growth in output in developing countries. This in turn leads to fears that convergence will generate huge increases in the world volume of greenhouse gas emissions. Against this, Castles and Henderson (2003 a & b) argue that comparisons of GNP per capita at MERs strongly understate output in developing countries relative to that in developed countries. As a consequence, convergence scenarios based on such comparisons strongly overstate the output growth in developing countries that would follow from convergence. Castles and Henderson suggest that comparisons of GNP per capita between developing and developed countries should be made in terms of purchasing power parity (PPP). A PPP of 2 for China and 1 for the U.S., for example, means that $US800 buys twice as much goods and services in China as it does in the U.S. Thus, output in China that is worth $US800 at the MER represents twice as much goods and services as output in the U.S. worth $US800. This in turn leads to the conclusion that convergence means a twenty-fold increase in Chinese output rather than a forty-fold increase. With smaller increases in output, the convergence hypothesis in PPP terms, at least at first glance, seems to imply a smaller increase in greenhouse-gas emissions than is implied by the hypothesis in market-exchange-rate terms. However, the first-glance conclusion is not necessarily right. If we assume that a country’s greenhouse-gas emissions per capita are a function of the real volume of its output per capita, then we might estimate greenhouse-gas emissions at convergence by assuming that emissions per capita in developing countries will converge to those in developed countries. Thus we could calculate the increase in world emissions by comparing the current level with the level that would apply if all developing countries were emitting at the same rate per capita as developed countries. The calculations could be made without even considering current differences in GNP per capita between developing and developed countries let alone worrying about whether these differences should be calculated in terms of MER or PPP. But the problem with this really simple approach is that different countries have different sources of energy and different climates. Thus, even if there were convergence in output per capita, it may not be reasonable to assume convergence in emissions per capita. So, how should we go about estimating the greenhouse-gas implications of convergence? Methodology: The method we investigate is simulation in a multi-country CGE model. We assume that countries have different GNP per capita mainly because they have different technologies (processes by which inputs are turned into outputs). We interpret convergence as meaning that technologies in developing countries become as efficient as those in developed countries. A CGE model is potentially an attractive vehicle for analysing the effects of technological change. Thus, under our interpretation of convergence, a CGE model is an attractive vehicle for analysing its effects. With technological differences as the starting point for an analysis in a CGE framework, controversies concerning inter-country comparisons of GNP are avoided. At the same time, the CGE framework is potentially rich enough in structural detail to encompass differences across countries in per capita emissions which would remain even after technological convergence. Data: 57 commodity by 3 region GTAP 5 database. Anticipated findings: Our modelling suggests four interesting conclusions. First, the MER/PPP distinction matters. In simulating the effects of convergence, we found that MER-based estimates of initial technology gaps lead to considerably higher estimates of convergence-induced growth in developing countries than do PPP-based estimates. Second, under convergence, the outputs of industries in developing countries will not grow as rapidly as their GDPs. This reflects intermediate-input-saving technical change. Third, for convergence analysis the industry detail in CGE models is valuable. Our simulations showed a wide range of convergence-induced changes in output across industries. Fourth, convergence by developing countries has only minor implications for consumption and GDP in developed countries. As well as suggesting potential conclusions about the implications of convergence, our modelling raises technical issues concerning PPP, real exchange rates, terms of trade and capital accumulation. References: Castles, I. and D. Henderson (2003a), “The IPC Emission Scenarios: An Economic-Statistical Critique”, Energy & Environment, 14 (2&3): 159-185. Castles, I. and D. Henderson (2003b), “Economics, Emission Scenarios and the Work of the IPCC”, Energy & Environment, 14 (4): 415-435. IPCC (2000), Emissions scenarios, special report of the Intergovernmental Panel on Climate Change, Nebojsa Nakicenovic and Rob Swart (eds.), Cambridge University Press, UK. |
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Last Modified: 9/15/2023 1:05:45 PM