Statistical Inference for the Aggregate Sources of Productivity Change Measured by Malmquist Productivity Indices

Léopold Simar (), Valentin Zelenyuk and Shirong Zhao
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Léopold Simar: Université catholique de Louvain, LIDAM/ISBA, Belgium

No 2026024, LIDAM Discussion Papers ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)

Abstract: The Malmquist productivity index (MPI) is one of the most widely used tools for measuring productivity change over time. A recent contribution by Pham et al. (2024) develops statistical inference procedures for the aggregate (or weighted) MPI of a group of firms. Building on this framework, the present paper develops statistical inference for the aggregate sources of productivity change measured by MPI. In particular, we derive the central limit theorems of the aggregated components, thereby enabling hypothesis testing for changes in technology, efficiency, and related sources. We illustrate the developed theoretical results by analyzing the sources of productivity change for 84 countries. Moreover, analogous theoretical results can be established for alternative productivity measures and their decompositions, including the Hicks–Moorsteen productivity index, the Luenberger productivity index, the Malmquist–Luenberger productivity index, etc.

Keywords: Data Envelopment Analysis; Malmquist Productivity Index; Aggregation; Central Limit Theorem; Efficiency Change; Technology Change (search for similar items in EconPapers)
JEL-codes: C12 C14 C43 C67 (search for similar items in EconPapers)
Pages: 31
Date: 2026-06-13
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Persistent link: https://EconPapers.repec.org/RePEc:aiz:louvad:2026024

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