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Stochastic Growth Models and Their Econometric Implications

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Abstract

This article considers the consequences of explicitly allowing for stochastic technological progress and stochastic labor input in the discrete-time Solow-Swan and AK growth models. It shows that the capital-output ratio, but not output per capita, is ergodic irrespective of whether there is a unit root in technology, and thus is the more appropriate measure to use in the cross-sectional analysis of the growth process. Furthermore, the article derives the cross-sectional and time-series implications of the stochastic Solow-Swan model and contrasts these to those of its deterministic counterpart. Among these implications are that the mean of the capital-output ratio depends in a precise way not only on the saving rate and the growth rate of labor input, but also on the variance and higher-order cumulants of the capital-output ratio. Using the Summers-Heston data for seventy-two countries from 1960 to 1992, strong support is found for the predictions of the stochastic Solow-Swan model as compared to those of its deterministic counterpart (as well as those of the AK model), including a significant negative cross-sectional relationship between the mean and the variance of the capital-output ratio.

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Authors and Affiliations

  1. Department of Economics, University of Maryland, College Park, MD

    Michael Binder

  2. Faculty of Economics and Politics, University of Cambridge, Cambridge, U.K

    M. Hashem Pesaran

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  1. Michael Binder
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  2. M. Hashem Pesaran
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Binder, M., Pesaran, M.H. Stochastic Growth Models and Their Econometric Implications. Journal of Economic Growth 4, 139–183 (1999). https://doi.org/10.1023/A:1009802421114

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