Forecasting the Malmquist productivity index
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Abstract
The Malmquist Productivity Index (MPI) suggests a convenient way of measuring the productivity change of a given unit between two consequent time periods. Until now, only a static approach for analyzing the MPI was available in the literature. However, this hides a potentially valuable information given by the evolution of productivity over time. In this paper, we introduce a dynamic procedure for forecasting the MPI. We compare several approaches and give credit to a method based on the assumption of circularity. Because the MPI is not circular, we present a new decomposition of the MPI, in which the time-varying indices are circular. Based on that decomposition, a new working dynamic forecasting procedure is proposed and illustrated. To construct prediction intervals of the MPI, we extend the bootstrap method in order to take into account potential serial correlation in the data. We illustrate all the new techniques described above by forecasting the productivity index of 17 OECD countries, constructed from their GDP, labor and capital stock.
Keywords
Malmquist productivity index Circularity Efficiency Smooth bootstrap Forecasting intervalsNotes
Acknowledgements
This work is supported by the contract “Projet d’Actions de Recherche Concertées” nr 07/12-002 of the “Communauté franaise de Belgique” granted by the “Académie universitaire Louvain”, and the IAP research network nr P6/03 of the Belgian Government (Belgian Science Policy).
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