Non-linear productivity and investment dynamics

Organised by

• Department of Economics

The nature of productivity shocks is a central feature of models of heterogeneous firm dynamics. Using firm-level data from Spain, we show that the observed productivity dynamics differ from those implied by the canonical, linear AR(1) representation with normally-distributed shocks. We document that the productivity process features non-linear persistence and non-normality. Motivated by this, we estimate a flexible stochastic process for productivity which allows for these features and compare its implications with the canonical one. We find that the flexible model fits the productivity data much better. We also estimate non-parametric, semi-reduced form empirical investment functions and find that the two processes imply very different responses to productivity shocks. Those estimated under the linear process imply, counterintuitively, that investment responds substantially more to transitory than persistent productivity shocks. Finally, we embed both the non-linear and the canonical process in a structural, partial equilibrium investment model and estimate capital adjustment costs under both specifications. The model estimated under the non-linear process fits the data much better and has very different implications for the relative importance of fixed versus quadratic costs of adjustment.

Co-authors: Beatriz Gonzàlez (Banco de España), Juan Carlos Ruiz-Garcia (Universitat de les Illes Balears) and Tatsuro Senga (Queen Mary University of London)