The seminar will be held in the Visitor Centre at 3:15 pm.
Eric Bartelsman (VU University, Amsterdam)
Abstract
This paper contributes to the productivity literature by using results from firm-level productivity studies to improve forecasts of macro-level productivity growth. The paper employs current research methods on estimating firm-level productivity to build times-series components that capture the joint dynamics of the .rm-level productivity and size distributions. The main question of the paper is to assess whether the micro-aggregated components of productivity. the so-called productivity decompositions. add useful information to improve the performance of macro-level productivity forecasts. The paper explores various speci.cations of decompositions and various forecasting experiments. The result from these horse-races is that microaggregated components improve simple aggregate total factor productivity forecasts. While the results are mixed for richer forecasting speci.cations, the paper shows, using Bayesian model averaging techniques (BMA), that the forecasts using micro-level information were always better than the macro alternative.
JEL classi.cation: C14, C23, D24, O12, O47
Keywords: economic growth, production function, total factor productivity, aggregation, panel data, forecasting