Stochastic structural change

Moro, Alessio;Rubini, Loris

2019-01-01

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Abstract

We propose a tractable algorithm to solve stochastic growth models of structural change. Under general conditions, structural change implies an unbalanced growth path. This property prevents the use of local solution techniques when uncertainty is introduced, and requires the adoption of global methods. Our algorithm relies on the Parameterized Expectations Approximation and we apply it to a stochastic version of a three-sector structural transformation growth model with Stone-Geary preferences. We use the calibrated solution to show that in this class of models there exists a tension between the long- and the short-run properties of the economy. This tension is due to the non-homothetic components of the various types of consumption, which are needed to fit long-run structural change, but imply a counterfactually high volatility of services, and counterfactually low volatilities of manufacturing and agriculture in the short-run.