Issues on Potential Growth Measurement and Comparison: How Structural Is the Production Function Approach?

By Cahn, Christophe; Saint-Guilhem, Arthur | Federal Reserve Bank of St. Louis Review, July-August 2009 | Go to article overview

Issues on Potential Growth Measurement and Comparison: How Structural Is the Production Function Approach?


Cahn, Christophe, Saint-Guilhem, Arthur, Federal Reserve Bank of St. Louis Review


This article aims to better understand the factors driving fluctuations in potential output measured by the production function approach (PFA.) To do so, the authors integrate a production function definition of potential output into a large-scale dynamic stochastic general equilibrium (DSGE) model in a fully consistent manner and give two estimated versions based on U.S. and euro-area data. The main contribution of this article is to provide a quantitative and comparative assessment of two approaches to potential output measurement, namely DSGE and PFA, in an integrated framework. The authors find that medium-term fluctuations in potential output measured by the PFA are likely to result from a large variety of shocks, real or nominal. These results suggest that international comparisons of potential growth using the PFA could lead to overstating the role of structural factors in explaining cross-country differences in potential output, while neglecting the fact that different economies are exposed to different shocks over time. (JEL C51, E32, O11, O47)

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International comparisons of potential output growth have received renewed interest in recent years. Lower economic performance in Europe compared with the United States over the past 15 years has generated several publications whose aim is to explain the sources of divergence in economic performance and which question how to enhance economic growth in Europe. In line with the recommendations of the Lisbon strategy, one general conclusion is that structural reforms should help to sustain more vigorous growth in Europe and enable European economies to catch up to the United States. Such reforms include labor and product market liberalization, public policies to encourage innovation, and so forth. Examples can be found in most recent International Monetary Fund (IMF) or Organisation for Economic Co-operation and Development (OECD) country reports on European economies. For instance, the 2007 IMF Article IV Staff Report for France (IMF, 2007) typically incorporates, among others, the important conclusion that "economic policy needs to address the root cause of France's growth deficit: the weakness of its supply potential." Against this background, it is important to have a clear view on how potential output is measured and what interpretation can be made of cross-country differences in potential output growth.

Among the different methods of measurement of potential output, the production function approach (PFA) is probably the most widely used. With this approach, output growth is expressed as a sum of the growth of factor inputs (i.e., capital services and labor input) and a residual (i.e., total factor productivity [TFP] growth). Additional assumptions are made on the potential level of the factors of production. For instance, potential labor input would be calculated by smoothing some variables (such as total population and the participation rate) and by approximating the medium-term equilibrium unemployment rate with the non-accelerating inflation rate of unemployment. The major advantage of the PFA, compared with statistical aggregate methods, is that it provides an economic interpretation of the different factors that drive growth in potential output. This is especially useful in the context of international comparisons. Moreover, conducting additional econometric analysis allows use of the PFA as a framework to capture the impact on potential growth of major changes, such as the pickup in productivity growth that started in the second half of the 1990s in the United States.

However, this approach raises some difficulties. Estimates of the components are bounded by a large degree of uncertainty because analysis results are highly dependent on the choice of modeling of the different components--for instance, how trend growth of TFP is estimated. Another difficulty derives from possible misleading interpretations of potential output as measured by the PFA. …

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