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Wan's “New Approach” to Technical Change: A Reply
Journal of Comparative Economics 27, 365–366 (1999) Article ID jcec.1999.1594, available online at http://www.idealibrary.com on
REPLY Wan’s “New Approach” to Technical Change: A Reply Guang Hua Wan 1 Department of Agricultural Economics, University of Sydney, Sydney, New South Wales 2006, Australia E-mail: [email protected] Received August 10, 1998; revised February 24, 1999
The comment by Felipe and McCombie (1999) raises an important, but old, question in economics. Can a production function be assumed when one interprets economic data? Should the answer be negative, many economic concepts would require fundamental modifications; some might even become totally irrelevant. However, the existence of a production function, although not necessarily an aggregate one, is a maintained assumption of Wan (1995). In addition, a constant-returns-to-scale (CRS) technology and constant relative factor prices are also assumed. As a consequence, Wan develops a method for measuring technical change from national income data that does not require the assumptions of competitiveness in both factor and product markets or the assumption of profit-maximizing behavior made in Solow (1957). Wan’s (1995) contribution lies in taking a dual approach to the measurement of technical change and it is in this sense that the paper was subtitled “A New Approach.” Technical change (TE) is defined as any change in a standard neoclassical production function allowing some observed level of output to be produced with fewer inputs, measured appropriately. The weaker behavioral assumption of cost minimization is all that is required, along with the above technical assumptions, for Wan to interpret the Solow residual as TE. This dual method is important for planned economies in which price controls are prevalent and production units are not profit-maximizing. In these economies, Wan’s dual approach of using the cost savings from a counterfactual, feasible input choice to produce observed output is a preferable way of measuring TE.
1
I thank the editor of the journal for his patience in handling the comment and my reply. 365
0147-5967/99 $30.00 Copyright © 1999 by Academic Press All rights of reproduction in any form reserved.
366
GUANG HUA WAN
Felipe and McCombie argue that both the Solow residual and Wan’s dual measure yield the same inappropriate measure of technical change because they can be derived by simply manipulating a national income accounting identity. Under imperfect competition, the accounting identity becomes Y 5 wL 1 rK 1 P, where P represents monopoly profit (Dornbusch and Fischer, 1987, p. 480). Although Wan’s (1995) measure can still be obtained by manipulating this accounting identity, it is no longer equivalent to the Solow residual unless P 5 0. Moreover, when substitution effects are incorporated, the measure of technical change resulting from Wan’s dual approach will be different from that resulting from other methods, including Solow’s, and this dual measure may not be derivable from an accounting identity (Wan, 1996). These points highlight the critical role played by behavioral and technical assumptions when the Solow residual and Wan’s dual approach are used as measures of technical change. To summarize, Felipe and McCombie seem to have missed the main point of Wan’s paper. For a country like China, and for any planned economy, assuming competitive markets and profit-maximizing behavior in order to use national income accounting data to make inferences concerning technical change is inappropriate. Wan’s dual approach is a better way to study this issue in China and in many other economies. REFERENCES Dornbusch, Rudiger, and Fischer, Stanley. Macroeconomics. Boston: McGraw–Hill, 1987. Felipe, Jesus, and McCombie, J. S. L., “Wan’s ‘New Approach’ to Technical Change: A Comment.” J. Comp. Econom. 27, 2:355–363, June 1999. Wan, Guang H., “Technical Change in Chinese State Industry: A New Approach.” J. Comp. Econom. 21, 3:308 –325, Dec. 1995. Wan, Guang H., “Measuring Input Substitution and Output Expansion Effects: A Nonparametric Approach with Application.” Empirical Econom. 21, 3:361–380, 1996.
REPLY Wan’s “New Approach” to Technical Change: A Reply Guang Hua Wan 1 Department of Agricultural Economics, University of Sydney, Sydney, New South Wales 2006, Australia E-mail: [email protected] Received August 10, 1998; revised February 24, 1999
The comment by Felipe and McCombie (1999) raises an important, but old, question in economics. Can a production function be assumed when one interprets economic data? Should the answer be negative, many economic concepts would require fundamental modifications; some might even become totally irrelevant. However, the existence of a production function, although not necessarily an aggregate one, is a maintained assumption of Wan (1995). In addition, a constant-returns-to-scale (CRS) technology and constant relative factor prices are also assumed. As a consequence, Wan develops a method for measuring technical change from national income data that does not require the assumptions of competitiveness in both factor and product markets or the assumption of profit-maximizing behavior made in Solow (1957). Wan’s (1995) contribution lies in taking a dual approach to the measurement of technical change and it is in this sense that the paper was subtitled “A New Approach.” Technical change (TE) is defined as any change in a standard neoclassical production function allowing some observed level of output to be produced with fewer inputs, measured appropriately. The weaker behavioral assumption of cost minimization is all that is required, along with the above technical assumptions, for Wan to interpret the Solow residual as TE. This dual method is important for planned economies in which price controls are prevalent and production units are not profit-maximizing. In these economies, Wan’s dual approach of using the cost savings from a counterfactual, feasible input choice to produce observed output is a preferable way of measuring TE.
1
I thank the editor of the journal for his patience in handling the comment and my reply. 365
0147-5967/99 $30.00 Copyright © 1999 by Academic Press All rights of reproduction in any form reserved.
366
GUANG HUA WAN
Felipe and McCombie argue that both the Solow residual and Wan’s dual measure yield the same inappropriate measure of technical change because they can be derived by simply manipulating a national income accounting identity. Under imperfect competition, the accounting identity becomes Y 5 wL 1 rK 1 P, where P represents monopoly profit (Dornbusch and Fischer, 1987, p. 480). Although Wan’s (1995) measure can still be obtained by manipulating this accounting identity, it is no longer equivalent to the Solow residual unless P 5 0. Moreover, when substitution effects are incorporated, the measure of technical change resulting from Wan’s dual approach will be different from that resulting from other methods, including Solow’s, and this dual measure may not be derivable from an accounting identity (Wan, 1996). These points highlight the critical role played by behavioral and technical assumptions when the Solow residual and Wan’s dual approach are used as measures of technical change. To summarize, Felipe and McCombie seem to have missed the main point of Wan’s paper. For a country like China, and for any planned economy, assuming competitive markets and profit-maximizing behavior in order to use national income accounting data to make inferences concerning technical change is inappropriate. Wan’s dual approach is a better way to study this issue in China and in many other economies. REFERENCES Dornbusch, Rudiger, and Fischer, Stanley. Macroeconomics. Boston: McGraw–Hill, 1987. Felipe, Jesus, and McCombie, J. S. L., “Wan’s ‘New Approach’ to Technical Change: A Comment.” J. Comp. Econom. 27, 2:355–363, June 1999. Wan, Guang H., “Technical Change in Chinese State Industry: A New Approach.” J. Comp. Econom. 21, 3:308 –325, Dec. 1995. Wan, Guang H., “Measuring Input Substitution and Output Expansion Effects: A Nonparametric Approach with Application.” Empirical Econom. 21, 3:361–380, 1996.